Excessive food waste (nearly 1.3 billion tons per annum) has exacerbated the world hunger crisis. This comprehensive review focuses on the food waste scenario, adverse effects, food waste management, existing waste management policies, and regulations in Bangladesh. Municipalities and urban centers generate 3.78 million tons of waste each year (15.96% of total food waste). This study utilized the national database to analyze food waste generation and projected growth by the year 2050. Yearly an estimated 17215.2 thousand acres of land and a significant amount of natural resources (water, energy) are being used to produce 23691.15 thousand tons of wasted food (45% of total food production). This study critically analyzed the waste management policy gap of Bangladesh and clearly identified each stage of the food loss production supply chain. The study assessed that yearly 481.6 MW energy could be generated from food waste. Focusing on effective policy and sustainability, a national food waste management model has been proposed for Bangladesh in compliance with sustainable development goals 12.3.1 global food loss. Food accumulates 16.7% to 20% of the world economy; therefore, any measures taken to reduce the food waste will be economically beneficial and environmentally sustainable. (C) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

This paper aims to establish consumers perception of electric waste recycling and management on a national scale in Bangladesh. The attitude, willingness to pay (WTP) and consumers behaviour were explored by conducting a questionnaire-based survey. The conclusions are based on 915 valid responses out of 2000 online survey invitations. Interestingly, 37.9% of the respondents indicated that they would accept to pay for electronic waste recycling. Analysis also shows that the preferred WTP would cover 5-10% of the recycling cost. Factors like environmental awareness, monthly income, and education level affect the consumers WTP. Nevertheless, most of the participants believe that the Government should share the recycling cost. The study suggests that e-waste recycling can be stimulated by promoting environmental awareness, educating the public about the benefits of recycling e-waste, and making e-waste recycling more convenient. However, additional measures will likely be needed to tackle the e-waste problem. Thus, support for environmental education is imperative in order to promote environmental awareness and increase the WTP of consumers. The study outlines key characteristics of consumer-focused e-waste management archetypes and proposes an effective road map for Bangladesh.

How can we use more of the materials and products that have already been produced? At the second hand shopping mall ReTuna in Eskilstuna, where circular flows are a reality, there are still many products going to waste. This master thesis project explores the possibilities of upcycle and repurpose driven design, and by that adding new value to existing products. The process of doing that is the basis of this report. 

ReTuna Återbruksgalleria is a place where people can leave products they do not want or need anymore.Everyday hundreds of products are left for reuse at ReTuna, which is connected to the overconsumptionthat results in copious amounts of second hand products. Much more than can be taken care of in today’s system. The resources put into every product needs to be valued accordingly to what they truly cost and emit. 

This master’s thesis project explores how to design within the planetary boundaries by taking care and responsibility for what already is produced.

The first phase of the project consists of observations and interviews to get an understanding of how ReTuna works. The framing of the project was decided after the research phase, which resulted in focus on one specific product, dining chairs. The next part of the project involves upcycling workshops, building of prototypes and an exhibition, all with a focus on increasing the value for second hand chairsand giving the material new areas of use. The last part of the project presents a design result, with an approach for involving more repurpose driven design and upcycling within design and product development.

Virtual Reality (VR) is a tool with great potential and is under constant development for use in new fields. The project Fabriksvisualisering (Factory Visualization), has within the digital factory field, developed a tool for companies to build their factories in Unreal Engine (UE) and VR. The tool gives companies the opportunity to test their factory layouts, before implementing in the real world, to avoid costly mistakes. The following report examines possibilities for users to simulate and visualize their factory workflows as a part of the project Fabriksvisualisering. To achieve this, different solutions for visualizing the flow of products, staff and vehicles have been explored. User tests were carried out to test how an effect from UE can be used to visualize a flow of products in VR. The result gives users the opportunity to experience the interactions with factory workflows and visualize how they flow in VR. 

The project resulted in two options that visualizes product flow and four options that visualizes workflow. Out of these six solutions, three were chosen and implemented to the project Fabriksvisualisering. These solutions are based on the construction of splines and include both alternatives for product flows and one alternative for workflows. The selection was based on functionality, user-friendliness and how realistic the outcome is. The result gives users the opportunity to experience the interactions with factory workflows and visualize how they flow in VR. 

The conclusion is that there are several ways to visualize four out of seven factory workflows. The flows that are possible to visualize are material handling of raw materials, semi-finished and finished products, as well as the transportation and movements of workforce. This can be visualized with the help of AI, a robot system within UE, the construction of splines and Niagara systems connected to splines.

When working under water at great depths, or in tough environments, remotely controlled underwater vehicles, so called ROV:s, are a good tool too use. With the help of these robots it is possible to work for longer periods of time and at larger depths then with ordinary divers. Ocean Robotics is a company from Linköping, Sweden, that has over 40 years of experience with ROV:s. They produce several different models for different kind of jobs.

The purpose of this project was to develop a concept of a device that keeps the tension constant on the tether that connects the ROV with the operator. The tension needs to be constant when the tether is being rolled in on and out from the winch. The work was executed on behalf of Ocean Robotics and a prerequisite was that it should be possible to integrate the device with the winch system they have today.

The work have followed Ulrich and Eppingers method for product development and together with requirements from the contractor several concepts was generated. The concepts were validated in a decision matrix and the concepts with the highest score was modeled in the CAD-program CREO Parametrics. The concepts got further developed and was compared against each other once again. Which generated the final concept. Furthermore a couple of friction tests were executed to find appropriate materials for the construction.

The final concept will be mounted on the winch and connected to Ocean Robotics self reversing screw. To measure the tension on the tether a load cell is used and the tether is fed by a rubberized wheel that is driven by an electric motor. To adjust the force around the tether a trapezoidal thread is driven by another electric motor, which adjust the pinch wheels height. The tether goes as a tangent between the two wheels that has a profile that insures that the force goes around the tether.  

Air intakes are complex components that are critical for the propulsion of the aircraft. The design has to consider requirements from several different departments, often contradictory. Additionally, the air intakes need to cooperate with other critical components. This makes testing of the models crucial, hence time-demanding. Design automation is a growing field which aims at minimizing repetitive work during product concept development. To follow the increasing digitalization, further investigations of design automation applied on air intakes are significant. 

The application Imagine and Shape in 3D Experience CATIA handles subdivided surfaces. These surfaces are both flexible and provide a high order of continuity, which is often desired. While design automation in CATIA is well investigated, design automation in Imagine and Shape is not. 

Knowledge based engineering techniques are often used to implement design automation. The methodology MOKA is frequently used when developing knowledge based engineering applications. This master thesis has followed MOKA in combination with Scrum. 

The master thesis has resulted in a method to allow automation in Imagine and Shape by linking mesh nodes on subdivided surfaces to reference points that are parameterized. Further, a method for generating air intake configurations as well as the integration with a fuselage has been developed. The method includes wireframe models in Generative Shape Design, subdivided surfaces in Imagine and Shape, scripts in EKL as well as UserForm and scripts in VBA. Additionally, the order of continuity for an integration between air intakes and fuselage has been analyzed using tools in 3D Experience CATIA. 

A conclusion drawn is that the method for generating air intakes cannot be completely automated. Instantiation and dimension of components can be automated, but manual work is required when using tools in Imagine and Shape during the integration between the components and the fuselage.Two methods for linking mesh nodes to reference points have been identified, one manual and one semi-automatic. The automatic method saves time and mouse clicks by utilizing VBA scripts. Further, the achieved order of continuity of an integration between subdivided surfaces depends on the individual components.

Public sector organizations have been increasingly turning to design in their pursuit to innovate and address pressing challenges that seem intractable through their existing ways of working. Design’s presence in the public sector is still a relatively recent phenomenon ridden with many challenges. Through a study of three municipalities in Sweden, we present tensions designers face as they work their way to build design capacity. We argue that making a place for design in organizational systems and their ways of working requires skillfully navigating these tensions. We describe each tension in terms of their contradictions embedded in dualities and discuss designers’ ways of managing them. Practical applications for design and public administration are also discussed.

Aircraft structural layout concept design at Saab Aeronautics utilize thickness optimizationto evaluate astructural layout concept. The thickness values can be used to compare conceptsto each other,and the bestonecan be further developed. Today, most ofthe creation and evaluation of structural layout concepts is manual work. Therefore, there is an ongoing investigation on how to implement design automation to reduce this manual and repetitive work.

The investigationaims to achieve rapid exploration of the design space to find a good base for a new aircraft development. This includes investigating how the synchronization between a structural layout model (SLM) and a global finite element model (GFEM) can be improved.

This thesis contributes to the investigation by exploring the possibilities to implement design automation in the creation of the SLM regarding the fuselage structure. Further, exploring the implementation of design automation in the creation of the GFEM to enable automatic evaluation of concepts. The thesis also explores how the synchronization between the models can be improved.

To structure the thesis work, the software development methodologies of MOKA and RAD weremodified and combined. The execution of the thesis was carried out in the software of 3DEXPERIENCE, particularly using the applications CATIAand SIMULIA.

This thesis work resulted in a methodfor developing and evaluating aircraft structure concept designs with design automation. The new method includes two models with corresponding scripts. The first model developed is a tool for a conceptualdesignerthat enables the creation of aircraft fuselage SLM from user defined inputs. The second model is generated by script which results in a GFEM with a direct connection to the SLM.

To conclude, the developed method enables a faster iteration work of fuselage structural concept designs compared to the current method. The detail level is lower but more consistent and uniform. The GFEM was not able to fulfil its purpose in the developed method due to time limits and software limitations. However, the synchronization between the SLM and GFEM was implemented successfully and contained all critical elements.

This master thesis report describes the development process of a modernized handguard for the AK4B battle rifle, which is the main armament for the Swedish Home Guard. The project was carried out in cooperation with ALTEN Sweden AB. The goal of the project was to develop a new, competitive handguard design and to establish a complete design documentation as a foundation for production. This documentation consisted of a final material selection, process plan with suitable manufacturing methods and engineering drawings. The project was initiated with a problem definition to establish a thorough understanding of the product to be improved and enabling a determination of aspects that might be of importance to the product development. From this, research areas could be selected and studied to acquire necessary insights to complete the project goals. The product development process implemented is mainly inspired by Ulrich & Eppinger, and includes the stages concept development, detail design and testing & refinement. Thus, well-established methodology was implemented, ensuring credibility and a qualitative result. Throughout the stages ofthe product development process, a product specification was established, before generating concepts and selecting a final candidate which were refined based on the selection of materials and elaborated process plan. Finally, a verification of the requirements was concluded using several methods to prove the performance of the product. The results presents a developed product fulfilling established requirements and includes required documentation for production. Overall, the product is considered to have great potential for customer satisfaction, and to perform well in a final testing according to military standards.  

Developing high-performing products at a low cost while keeping development time down is increasingly important in today’s competitive market. The current state presents a need for efficient product development processes. One of the challenges is knowledge often being limited in early stages where the cost of making changes is still relatively low. As the process progresses more knowledge is gained to better support decisions; however the cost of making changes increases, limiting the design freedom. To increase knowledge while retaining design freedom, several computer-based tools are available to both generate and evaluate designs in order to make iterations faster and more accurate.

Design Optimization (DO) can be utilized to explore the design space and find optimal designs. A Computer-Aided Design (CAD) model is often required as input to analysis tools evaluating the designs. By utilizing Design Automation (DA) several tasks involved in creation and modification of CAD models can be automated. For this reason, DA is sometimes considered an enabler for DO although its use is far wider, covering several aspects of the design process mainly focusing on automating repetitive and routine tasks.

Machine Learning and other data-driven methods are becoming increasingly viable in the context of DO and DA. This thesis explores the use of data-driven methods to enhance the usability of DO in different ways such as a faster process, new use-cases, or a more integrated and automated process.  

Literature in the area is reviewed, identifying applications, trends and challenges. Furthermore, two support tools are developed, incorporating data-driven methods tied to an industrial case. The applications focus on parameterizing geometry and predicting design performance respectively. Potential benefits, limitations, and challenges are discussed based on the literature review and insights from the two support tools. The focus of the thesis is mainly on how data-driven methods can facilitate automation and integration in the design process, specifically for complex products requiring significant engineering efforts.  

Cable and hose routing is a complex and time-consuming process that often involves several conflicting objectives. Complexity increases further when routes of multiple components are to be considered through the same space. Extensive work has been done in the area of automatic routing where few proposals optimize multiple hoses together. This paper proposes a framework for the routing of multiple pre-formed hoses in an assembly using a unique permutation process where several alternatives for each hose are generated. A combinatorial optimization process is then used to find Pareto-optimal solutions for the multi-route assembly. This is coupled with a scoring model that predicts the overall fitness of a solution based on designs previously scored by the engineer as well as an evaluation system where the engineer can score new designs found through the use of the framework to update the scoring model. The framework is evaluated using a testcase from a car manufacturer showing a severalfold time reduction compared to a strictly manual process. Considering the time savings, the proposed framework has the potential to greatly reduce the overall routing processes of hoses and cables.

In order to enable easy modification of results from a design optimization process in a CAD tool, a flexible representation of the geometry is needed. This is not always trivial however, since many file formats are not importable as modifiable geometry into the CAD tool, and if they are, they might not represent the geometry in a way that enables easy modification. To mitigate this problem a design automation (DA) and a machine learning (ML) approach are developed and compared using a test case from an optimization process used to optimize hose routing in tight spaces. In the test case used, the geometry from the optimization process consists of center curves represented as a large number of points. To enable easy modification a more flexible representation is needed such as a spline with a few well-placed control points. Both the DA and ML approach can approximate center curves from the optimization process as splines containing a varying number of control points but do show different properties. The DA approach is considerably slower than the ML but adds a lot of flexibility regarding accuracy and the number of control points used.

Material Driven Design, or MDD, is a new way of realizing products starting in the understanding ofthe material rather than the need-driven approach that can be used to describe classic productdevelopment methodology. While new, MDD has potential to encourage more sustainable productsbeing developed and is a useful tool for new designers and engineers to learn. In this paper, the authorpresents some lessons learned from teaching MDD to students in design and product development at aSwedish university. These students have experience from design and product development projects buthave not done material-driven projects before. In general, the author concludes that the students areremarkably well-prepared in terms of tools and knowledge to do MDD, but that course coordination canmake the projects less efficient if this is not solved early on. In master thesis projects or courses withfew in-process deliverables, the implementation seems easier and can give students another path to solveproblems in industry.

On the path towards a circular economy, new ways of making and producing must be implemented on an industrial level. While there are methods for remanufacturing, the topic of repurposing on an industrial scale is still not fully explored and systematized. Repurposing, in this paper defined as the process of re-using products or components but with other functions, or modifying products or components for use in other products, will have a distinct effect on the production system and will challenge the current idea of production system development. In this paper, the authors use four different cases (three implemented in industry, one current design project in an academic-industrial partnership) to reflect on how the production system will be affected by certain aspects of repurposing. In total, five topics of production system development (Material classification, Product definition, Logistics & material handling, Manufacturing processes & planning and Processing window) are highlighted in the analysis, and some concluding remarks about flexibility needs and integrated development processes are presented. This paper does not provide clear answers or methods on how to implement repurposing but highlights multiple areas where further research is needed in order to make repurposing easily accessible and possible to implement for small and medium-sized manufacturers in their regular, daily work.

The remanufacturing industry currently relies significantly on manualwork when, for example, sorting and disassembling. Due to several issues, includingprocess time and sequence, operations number, disassembly planning andscheduling, process cost, and performance measurement, it is challenging to staycompetitive. Based on this, it is assumed that more extensive use of robots andautomation in these industries can facilitate higher efficiency and better workconditions. This research paper aims to explore how remanufacturing of carcomponents can be made automatic. The paper describes a case where a specific carcomponent was selected and a specific step in its remanufacturing process exploredfrom the perspective of automating that task. When conducting remanufacturing ofthe selected car component, some machines are used for the testing, cleaning, andgrinding of materials. However, all assembly work is done manually. Incollaboration with the case company, the process step of applying sealant for theassembling of a lid that covers electronic components was selected. Thedemonstrator shows that it is possible to apply sealant with a human-robot layoutwith a good result. One of the advantages of using a robot for this step is that a highquality result was achieved. 

Drying is a complicated phenomenon involving a combination of transport, deformation, and chemical kinetics. It is an energy intensive lengthy process and results in deterioration of food quality. The glass transition temperature (GTT) significantly affects the internal mass transfer mechanism and hence significantly affects the drying kinetics. Moreover, the rheological and transport characteristics of food materials are remarkably impacted by GTT, which has an influence on the energy consumption and quality of food products during drying. Similarly, molecular weight and drying conditions also affect the GTT. This comprehensive review uncovers the fundamental understanding of GTT and demonstrates its crucial relationship with physio-structural and transport properties of food items. It has been demonstrated that a clear understanding of the glass transition temperature may help in determining appropriate drying conditions while ensuring great food quality.

Graphene is a two-dimensional carbon based material with unique properties, such as electrical and thermal conductivity. When a textile is coated with graphene, it becomes conductive, while remaining low weight, soft, breathable, flexible, and stretchable. The purpose of this thesis is to investigate what products are suitable to be made with graphene textiles, by using the method Material Driven Design (MDD). Reflections are also made to determine how this method is affected by being applied to a two-dimensional material. To help with this, three kinds of graphene textiles from the company Grafren AB are investigated; conductive textiles, heatable textiles, and textile sensors. The product goal is to develop a portfolio containing 5-8 conceptual products based on these graphene textiles.

The process includes conducting an investigation of the technical properties of the material, a user study, and a benchmarking study. This is done to understand the limitations and opportunities of the material, how it is perceived, and what similar materials there are on the market. After that, the material's characteristics are reflected upon to establish a vision for how it should be used in future applications. Then, to follow that vision, a user study is conducted to investigate how people perceive different materials and products, in order to create design guidelines to ensure that the material and product are perceived as intended. Next, concepts are developed according to the previously determined guidelines. To achieve this, idea generating workshops are conducted, where 14 concepts are selected for further development. The portfolio is then created, meant to inspire further usage of the material. It contains the following seven concepts.

1. A heatable textile meant for cooking on camping trips.
2. A fabric containing sensors that can notify when it is damaged.
3. A keyboard made of fabric, for an easy and comfortable use and transportation.
4. A stroller with sensors and heaters, for a more comfortable and safe user experience.
5. A conductive jacket that can electrocute mosquitoes that come in contact with it.
6. Pressure sensors in a carpet that can keep track of the people inside and provide assistance in emergencies.
7. Gloves with sensors in them that can translate sign language live to text or speech.

Since MDD heavily focuses on the sensorial qualities and physical characteristics of the material, the method needs to be adapted to become useful when working with such a versatile two-dimensional material. Fortunately, most adaptations can be made fairly easily. The timing of each step should also be considered, to ensure that the vision and guidelines can be made specific enough to be useful.

Scania is known as a front-runner in the development of power trains for heavy vehicles, marine, and general industrial applications. As the regulations on emissions for combustion engine vehicles are getting tougher with increasing awareness on sustainable solutions and reducing environmental impact, the goal at Scania is to develop combustion engines to achieve low-pollutant emissions whilst achieving higher efficiency. Consequently, the exhaust after-treatment systems must continuously evolve to meet changing legislative requirements and customer demands.  To achieve this goal in this competitive market, Scania must adapt to these changes within a short period of time.

The purpose of this thesis is to explore and improve the existing development process for the exhaust after-treatment system particularly for Large silencer platform by introducing design automation intended for computational fluid dynamics simulations. The objective was to introduce a method to reduce development time and allow designers to generate CFD models as effectively as possible.

Two new methods were developed and proposed to create geometries intended for CFD simulation. The first method focuses on the extraction and splitting of internal volume/fluid region and these models will be utilized in the simulation solvers to perform CFD simulation. The second method was to standardize the naming of extracted surfaces specific to CFD simulation since every surface is treated differently in the simulation solvers. A simple user-friendly graphical user interface was created for easy operation and faster adaptability.

Finally, the developed methods were evaluated and it was shown that it has the potential to save a significant amount of time during the pre-processing of the development phase and thus allow the engineers to focus on other value-adding and important task.

Harvesting heads are an essential part of today’s forestry industry, enabling a high rate of tree felling from a single operator. Requirements for the forestry machine they are attached to are strongly linked to the weight of the harvesting head, providing an incentive to make the heads as light as possible. This can be done in various ways, of which one is switching the material to one that is lighter.This thesis examined the feasibility of producing the frame of a harvesting head in carbon fiber reinforced polymer. This was done through a redesign approach in several phases. The design and requirements of the existing harvesting head were detailed, the strengths and weaknesses of the material were studied, and topology optimization was utilized as a tool for better understanding the load paths and possible material placement. Concepts aimed at enabling production and use of the new frame while keeping features necessary for component attachment and function was then generated.The results showed a frame made largely from carbon fiber reinforced polymer, but with elements of steel, and with a total weight reduction of 45% compared to the original design. The conclusions of the thesis, within the established delimitations, is that a frame from this material is possible but complex to produce.

The field of design automation aims to automate repetitive tasks in a workflow in order to free up time for more productive work. In this thesis, design automation with the help of AI techniques is investigated to streamline the pre-production work of expanded metal facades. 

Two different problems concerning pre-production work are investigated in this thesis. The first one focuses on how to translate architectural drawings in pdf format to a bill of material. The second problem aims to develop a non-linear method for calculating the free area of the expanded metal facades.

The method used for this project is an adaptation of the product development process with the inspiration of knowledge-based engineering. 

For the first project, the AI method template matching was successfully used. With a script using this method, most of the panels are identified, except for panels where the drawings do not provide clear lines or where lines around the panels do not exist. The line quality in the architectural drawings was shown to impact the size estimation of the panels.

In the second project, a non-linear machine learning model was developed. However, it was not managed within this project to get a good enough accuracy. The main reason for this is that it is suspected that the data is not accurate enough, nor are the 78 data points enough to train the model.

Intermittent microwave-convective drying (IMCD) is an advanced drying technology that overcomes the shortcomings of microwave, convective, and microwave-convective drying. Research on the feasibility study of solar-assisted IMCD along with investigating its microstructure change, nutritional analysis, and appearance of dried food materials is inadequate. This research aims to investigate the effects of microwave intermittency-on quality attributes and structural changes of potato slices. In addition, optimization of pulse ratio has been performed in this study. Drying experiments, namely convective drying (CD) and IMCD, were conducted to assess the quality of dried potato slices. It was found that IMCD took only 12 min to complete the drying process, whereas CD took approximately 300 min. The optical (colour) and nutritional (vitamin C) properties of the IMCD dried potato slices appeared better than those of hot air-dried samples. The overall techno-economic analysis indicates that the proposed solar-assisted IMCD can dry an equal amount of potato while consuming one-tenth of the required energy of CD. Therefore, successful industrial application of the proposed drying system might be a stepping stone in the way to the advancement of energy-efficient food drying systems.

The AK4 rifle serves as the primary weapon for the Home Guard, an integral part of the Swedish Armed Forces. Introduced in 1964, the AK4 is the Swedish version of the Heckler & Koch G3 and functions as a fully automatic assault rifle. Among its components, the handguard holds significant importance, providing stability, improving accuracy and control, and protecting the user from heat generated by the barrel. Recognizing the need for optimization, an employee from the ALTEN Group, possessing military experience and expertise in the AK4, launched a project to enhance the ergonomics and versatility of the handguard in a cost-effective manner. This initiative stems from the excessively high cost of commercially available handguards, making them financially unviable for replacing the original handguard of every AK4 used by the Home Guard personnel.

This project aims to design and develop a next-generation handguard for the AK4 rifle that addresses the current limitations of the existing handguard. The primary focus is improving the shooter’s performance by establishing a comfortable shape of the handguard, reducing the weight, and enhancing its compatibility with accessories. Additionally, the aim is to ensure the handguard is cost-effective for mass production and meets the requirements set by the Swedish Defense Materiel Administration. To achieve the aims, interviews and a comprehensive user testing study was conducted, collecting quantitative data in the form of participant ratings and rankings for different design concept while also gathering qualitative data through participant feedback that highlighted specific design features contributing to comfort. Additionally, a systematic material selection process was performed, involving the analysis and ranking of various materials based on properties such as weight, price, and specific mechanical properties. Furthermore, the manufacturing analysis relied mainly on conversations with industry experts possessing expertise in the field of plastic manufacturing.

Upon conducting a detailed analysis, it has been determined that the ideal configuration for the final product is an octagonal shape. After careful evaluation, Polyamide 6 reinforced with 30% glass fibers has emerged as the most suitable material choice for the handguard. This material had the optimal balance between mechanical properties, thermal performance, durability, cost-effectiveness, and environmental impact. To produce 50,000 handguard units, the recommended manufacturing method was injection molding due to its compatibility with mass production and the advice received from industry experts. Considering the design and selected material, a substantial number of the requirements outlined by FMV could be fulfilled by conducting both theoretical analyses and practical experiments.

This paper presents a framework to develop the automated design of fixtures using the combination ofdesign automation (DA), multidisciplinary optimization and robotic simulation. MDO necessitates the useof concurrent and parametric designs which are created by DA and knowledge-based engineering tools. Thisapproach is designed to decrease the time and cost of the fixture design process by increasing the degree ofautomation. AutoFix provides methods and tools for automatically optimizing resource-intensive fixturedesign utilizing digital tools from different disciplines.

Implementation of Machine Learning (ML) to improve product and production development processes poses a significant opportunity for manufacturing industries. ML has the capability to calibrate models with considerable adaptability and high accuracy. This capability is specifically promising for applications where classical production automation is too expensive, e.g., for mass customization cases where the production environment is uncertain and unstructured. To cope with the diversity in production systems and working environments, Reinforcement Learning (RL) in combination with lightweight game engines can be used from initial stages of a product and production development process. However, there are multiple challenges such as collecting observations in a virtual environment which can interact similar to a physical environment. This project focuses on setting up RL methodologies to perform path-finding and collision detection in varying environments. One case study is human assembly evaluation method in the automobile industry which is currently manual intensive to investigate digitally. For this case, a mannequin is trained to perform pick and place operations in varying environments and thus automating assembly validation process in early design phases. The next application is path-finding of mobile robots including an articulated arm to perform pick and place operations. This application is expensive to setup with classical methods and thus RL enables an automated approach for this task as well.

This thesis covers the process of automating the design of coolant nozzles used for cylindrical grinding. Coolant nozzles are used to supply coolant, an oil and water mixture used to cool the metal workpiece and lubricate the grinding wheel. In the automotive industry, grinding is used to reduce the surface roughness of the workpiece. However, a large amount of heat is generated, risking the heat treatment of the steel to be compromised, for this, coolant is supplied to minimize the heat caused by friction. A nozzle is used, aiming a jet to the zone that generates heat. Commonly used nozzles are adjustable, leading to variation in cooling performance if misaligned. The design of fixed nozzles is developed in this thesis to reduce variation and automatise the design for multiple applications. The automatically designed nozzles are fused deposition modeled and tested. The design automation tool is tested repeatedly and improved successively in the span of the thesis. This lead to a great extent of implementation of design automation. Which lead to a facilitation in reaching of the work zone and avoid obstacles. Also, the tool managed to create nozzle tubes for a multitude of machines. The tool is able to generate, aim, orient, and individually dimension multi-nozzle tubes. Design of Experiment methodology is implemented to find nozzle designs with improved velocity and flow rate and minimize the air mixture with the coolant. Several nozzle designs are tested and fitted into a surrogate model that is, in turn, optimized. The results of the tests led to a greater understanding of how the nozzle geometry restricts the flow rate when attempts of reaching higher velocities of the coolant jet are made. The surrogate models created, also made it possible to find the range of designs which best suits different applications, whereby a Pareto front was able to be populated with a range of different designs alternating in flow rate, velocity and coherency ratio.

Introduction: As the increase in electrification poses new demands on power delivery, the quality of the distribution system is paramount. Substations are a critical part of power grids that allow for control and service of the electrical distribution system. Substations are currently developed in a project-based and manually intensive manner, with a high degree of manual work and lengthy lead times. Substations are primarily sold through tenders that are accompanied by an inherent need for engineering-to-order activities. Although necessary, these activities present a paradox as tender processes must be agile and fast. To remedy this shortcoming, this article outlines a knowledge capture and reuse methodology to standardize and automate the product development processes of substation design.Methods: A novel framework for substation design is presented that implements knowledge-based engineering (KBE) and artificial intelligence methods in computer vision to capture knowledge. In addition, a product configuration system is presented, utilizing high-level CAD templates. The development has followed the KBE methodology MOKA.Results: The proposed framework has been implemented on several company cases where three (simplified) are presented in this paper. The framework decreased the time to create a 3D model from a basic electric single line diagram by performing the identification and design tasks in an automated fashion.Discussion: Ultimately, the framework will allow substation design companies to increase competitiveness through automation and knowledge management and enable more tenders to be answered without losing engineering quality.

The aerospace industry has a long tradition of using Model Based Systems Engineering in its development processes. Throughout the years an extensive library of system simulation models has been created, expanding with every new model being developed. Nevertheless, modelling and simulation engineers prefer developing their own models from scratch, as the reuse of legacy models seems cumbersome, leading to the simultaneous existence of multiple simulation models of the same system in a project. Not only does the development, verification and validation and maintenance of these multiple simulation models incur extra costs, but they also represent a potential threat to the aircraft development, as data consistency is more difficult to be ensured. 

The aim of this thesis is to investigate simulation model reuse during the aircraft development process, with the goal of creating an easy-to-reconfigure simulation framework, allowing for the inclusion of simulation models of various levels of fidelity. Through an industry-as-laboratory approach, the inclusion of industry-grade legacy system simulation models is investigated, with the help of simulation model integration standards such as Functional Mock-up Interface and System Structure and Parametrisation. 

The results of the work include the development of a proof-of-concept simulation framework that enables the aggregation, integration and reuse of simulation models from different technological domains and with different levels of fidelity. Moreover, the work proposes a workflow that streamlines the decision milestones when faced with the possibility of selecting between creating a new system simulation model or reusing a legacy one, and highlights the challenges associated with model reuse from both a technical and an organisational perspective. 

This paper presents and analyses the research front on development methodologies that can be applied to flight simulations for development purposes. This field includes any flight simulator used during the development phase of an aircraft, when flight test or other validation data is still scarce. A review of the literature published between 1999-2019 is performed. As flight-specific literature on the topic is limited, a broader view on flight simulators is adopted. Simulators are regarded as risk-averse scientific software; that is, software created to understand a phenomenon and whose primary goal is to be correct. This perspective highlights the lack of suitable established software development methodologies (SwDev) for this software type. Two solutions to this problem have been identified: one treating scientific SwDev as a knowledge acquisition process, and another one treating it as development of enabling systems, following the established product development processes. These solutions need to be completed with methodologies to deal with the multidisciplinarity of the flight simulation problem, such as model exchange standards or workflows for multidisciplinary collaboration.

This study presents a solution for connecting system simulation and aircraft concept development using solely open standards. An easy-to-use optimisation framework for aircraft concept development is created with the help of the Modelica, Functional Mock-up Interface (FMI), and System Structure and Parameterization (SSP) standards, and the open source tools OpenModelica and OMSimulator. The framework allows for conceptual aircraft design accounting for transient phenomena by means of standardised integration of dynamic simulation models of aircraft subsystems. The framework is applied to an industry-relevant use case concerning the concept development of a generic fighter aircraft. The generality and modularity of the framework and its straightforward implementation enables tailoring of the optimisation goals to the user needs and requirements. The adoption of industry-wide standards allows for the inclusion of system simulation models developed in the modelling tool best suited for each discipline, thus integrating dynamic system simulation already at the aircraft conceptual design stage.

Increased industrial interest in mass customisation causes designers and manufacturers to seek cost-effective methods to continuously rationalise product development and production processes in order to accommodate for customisation on a large scale. Particularly in the case of complex products this requires significant engineering efforts. 

Mass customisation in an engineer-to-order context includes customers in early stages of product development, providing designers and manufacturers with certainty in decision making. A large portion of design tasks associated with design and production preparation stages during the product development process are routine-like and repetitive, amounting to vast time costs and errors. By utilising knowledge-based design automation techniques, these tasks can be supported to allow for iterative design processes as well as improved integration and communication between development phases. This  work explores how the use of design automation in the form of product configuration systems can facilitate integration throughout the product development process of engineer-to-order products and allow the industry to rise to the challenge of mass customisation.

This licentiate thesis describes the development of a framework incorporating product configuration systems based on High Level CAD templates (HLCt) together with auxiliary design optimisation and production preparation tools. Leveraging on the reuse of product knowledge, it focuses on rapid configuration of light-weight conceptual designs for quotation in dialogue with customers, and support of detailed design and generation of production data for confirmed orders. Based on the findings from implementation of such framework in an SME context of mass customisation of spiral staircases as well as engineering education, the challenges and possibilities are discussed with an eye on the future of design automation for mass customisation.

Maintaining high product quality while reducing cost is essential for mass-customised products, requiring continuous improvement of the product development process. To this end, design automation should be utilised in all stages of a product’s develop process and lay the foundation for automation of repetitive tasks throughout the process from interaction with the customer to design and production in order to mitigate errors and minimise costs. In this paper, a design automation and production preparation framework is proposed that can facilitate automation from initial stages via CAD to production. Examples of the framework are shown in the shape of proof-of-concepts systems developed by master students in the context of a course in design automation at Linköping University. Included disciplines such as automated planning of robot assembly paths, CNC manufacturing files and production drawings are described, based on design automation, Knowledge-Based Engineering, and design optimisation. Additionally, variations of the framework are implemented at three SMEs, and the results thereof are presented. The proposed frameworks enable interaction and connection between the "softer", human centred, aspects of customer interaction within sales, with more traditional "harder" engineering disciplines in design and manufacturing.

Historically, table tennis blades have been subject to few changes. Apart from the introduction of a few new materials, such as carbon fibre, resulting from rule changes in the sport, the pace of change has been slow. This project is based on three cases containing potential rule changes to the regulations of the sport regarding the construction of blades. Furthermore, the sport, its user’s needs, and potential new materials to implement have been investigated, resulting in the development of a series of prototypes. A total of 21 prototypes have been used with the aim of improving the control properties of the blade, which along with speed and spin are considered the most important playing characteristics in a table tennis stroke. The overall result from user tests indicates that three of the prototypes possess interesting properties which should be investigated further, out of which two are presented in this report. These prototypes consist of a prototype where a layer of the fibrous material Vectran is included, and a prototype where a layer consists of a honeycomb structure made of the material Nomex, and a third prototype that upon request from the company has been decided to be excluded from the report. Finally, recommendations for further development of these prototypes are described. 

Packing products into a pallet or other medium is an unavoidable activity for producing companies. In many cases, packing is based on operator experience and training using packing patterns that have worked before. Automated packing, on the other hand, requires a systematic procedure for devising packing solutions. In the scientific literature, this problem is known as 3D bin packing (3DBP) and many authors have proposed exact and heuristic solutions for many variations of the problem. There is, however, a lack of datasets that can be used to test and validate such solutions. Many of the available datasets use randomly generated products with extremely limited connection to real practice. Furthermore, they contain a reduced number of product configurations and ignore that packing relates to customers orders, which have specific relative mixes of products. This paper proposes a software toolbox for generating arbitrarily large datasets for 3DBPP based on real industry data. The toolbox was developed in connection with the analysis of a real dataset from the food and beverages sector, which enabled the creation of several synthetic datasets. The toolbox and the synthetic datasets are publicly available and can be used to generate additional data for testing and validating 3DBP solutions. The industry is increasingly becoming data dependent and driven. The ability to generate good quality synthetic data to support the development of solutions to real industry problems is of extreme importance. This work is a step in that direction in a domain where open data are scarce.

The description of structure and complex interactions in Multi-agent-based Industrial Cyber-physical (MAS-ICPS) systems has been elusively addressed in the literature. Existing works, grounded on model-based engineering, have been successful at characterizing and solving system integration problems. However, they fail to describe accurately the collective and dynamic execution behaviour of large and complex industrial systems, particularly in more discrete production domains, such as: automotive, home appliances, aerospace, food and beverages, etc. In these domains, the execution flow diverts dynamically due to production disturbances, custom orders, fluctuations in demand in mixed model production, faults, quality-control and product rework, etc. These dynamic conditions require re-allocation and reconfiguration of production resources, redirection of production flows, re-scheduling of orders, etc. A meta-model for describing the structure and complex interactions in MAS-ICPS is defined in this paper. This contribution goes beyond the State-Of-The-Art (SOTA) as the proposed meta-model describes structure, as many other literature contributions, but also describes the execution behaviour of arbitrarily complex interactions. The previous is achieved with the introduction of general execution flow control operators in the meta-model. These operators cover, among other aspects, delegation of the execution flow and dynamic decision making. Additionally, the contribution also goes beyond the SOTA by including validation mechanisms for the models generated by the meta-model. Finally, the contribution adds to the current literature by providing a meta-model focusing on production execution and not just on describing the structural connectivity aspects of ICPSs.

Prototyping is a crucial element of the design activity. Prototypes serve as temporary and incomplete embodiments of design ideas with which designers explore the design problem as well as propose and refine possible solutions to the problem. Given its deep connection to solutions, prototyping has been typically associated with the later stages of design. A stage in which the problem has been sufficiently mapped that a solution can be proposed and refined based on the discovery of requirements. Yet the question of what it means to prototype for problem exploration remains. To provide an answer to this question, first we take a quick look at what the role of prototypes is in design and more specifically what their role might be in the early stages of design. And later we discuss from the perspective of the reflective conversation that the designer has with the artifact it has created and what we reflect on when dealing with problem exploration. Subsequently some illustrative examples are presented of unintentional problem exploration prototyping from student design projects. To conclude, a reflection of the importance of design education in preparing practitioners to better deal with different types of prototyping beyond solution refinement. 

Studying Systems of Systems (SoS) in relation to Measures of Effectiveness (MoE) is a difficult task. This is due to that SoSs include several system levels and operate in changing environments. There are also computational challenges related to modeling and simulation of SoSs and it is difficult to predict behaviors. Therefore, choosing model fidelity for system models and assessing their impact on MoE is of high relevance to the field. This paper illustrates an approach to modeling and simulation for SoSs that can be used to assess the impact of scenario parameters and to explore when level of fidelity on system level affects the MoE. This is made through a case study based on Search and Rescue (SAR) operations where a Design Of Experiments (DOE) of scenario parameters is performed and simulations of each scenario experiment is performed. The case study shows how Agent Based Simulations (ABS) can be used to obtain the MoE for different SAR missions and how the choice of model fidelity for one of the aircraft’s sensors has different effects for various scenarios. Additionally, a Visual Analytics (VA) approach is introduced and used to create a dashboard for visualizing the obtained simulation results in an interactive way. This allows users to make explorations on the resulting data and see how different scenarios influence the performance of each SoS. Furthermore, the results show that changes in scenario parameters impacts the MoE and that this is difficult to predict, at least using a quantitative method. The results point to the importance of exploration for both the scenario, using an interactive dashboard, but also to the importance of exploring the simulation model to study emerging phenomenon. The results of this approach have raised questions regarding if a more qualitative approach of studying SoSs could be beneficial to study MoE for SoSs and if inspiration could be transferred from a more scientific point of view of systems.

The methodology of Kansei Engineering can grasp consumer???s subjective affective impressions about a product and turn it into concrete product solutions. The Kansei Food model is a specialized model doing this for food products. The aim of this paper is to interlink it with the more general model on Affective Engineering as well as to validate the findings by applying them in a case study. The general Kansei Engineering model and the Kansei Food model were analyzed, and the key parts of both models merged to a hybrid model. This model is then applied in a study on a development project for chocolate toffee fillings for sport applications. The case yielded valid results and gave an input to a parallel food development process. In conclusion, the Kansei Food model fits together with the general Kansei model. Hence, standardization makes it possible to have a more detailed look on sequential steps. Also, it becomes possible to transfer tools from other branch models (e.g. from automotive industry) in food industry and vice versa.

This thesis is a human-centered concept development in lighting. The purpose of the work was to show the possibility of how lighting could be used and how lighting is applied to have the desired effect during night driving. The purpose of the customer was a user-friendly machine. The goal was to deliver knowledge in lighting to Väderstad regarding their agricultural machines. There were three product groups, all of which were carefully examined. Ideas in design-, user- and indication-lighting were presented.

The question that was answered in the essay was: What are the most important lighting functions for farmers on seed drills from Väderstad with a focus on night driving?

The methodology was taken from two engineering design processes and a lighting design process. Initially, it was problem finding and information gathering to gain a good understanding of the work and what was desired, then a creative phase with concept development that generated different ideas for possible solutions. This was followed by a mid-term meeting where concept selection was in focus. Finally, a lighting plan was created that became the appearance and function of the end result.

The theory describes the technical possibility that LED lighting has created. With cheaper and more accessible technology, increases the number of users and more uses for light. This development is not only positive, but also brings light pollution that is negative for humans and animals. The physiology of the eye and how it comes about that the brain "sees" as well as visual changes that are linked to age are also described in the theory chapter. Finally, various forms of light environments and the risk of injury and accidents are described, including blinding and flicker.

The end result was a concept of luminaires applied to the machine. Better lighting in the seed box and on platforms and steps is presented in rendered images on the Inspire 1200 C / S machine.

Husqvarna Construction is one of the leading construction machinery manufacturers in the world. To stay in the forefront, investing in novel methods to model, test & and optimize machinery is crucial. The most important part of development and testing is to bridge the gap between desired and actual results. Model-based Simulation in testing plays a superior role in visualizing possibilities while cutting down the usage of resources.

Floor Grinders are common in industrial and commercial settings to achieve desired floor results. Like every machinery, optimization towards achieving better results is a necessity. The purpose of this thesis is to develop a methodology to optimize Husqvarna Constructions’s floor-grinding machine through its grinding pattern and further study & gather data about the key indicators for an optimum grinding pattern. This is done by setting up a grinding pattern simulation of the PG 690 floor grinder on SIMGRIND (Husqvarna Construction’s own simulation application).

A metric was developed to determine whether a grinding pattern is good, and by utilizing the metric as an optimization goal, the impact of different machine parameters on the grinding pattern was established. The grinding & travel speeds were viewed as ratios and it was observed that optimized patterns were attained at particular ratios. Another crucial factor that was studied was the impact of oscillations. Further, the impact of grinding head size on the grinding pattern was also studied.

The investigation was limited to a simulation study since physical validation opened up several uncertainties beyond the scope of this work. At the end of this work, a few recommendations for developing physical validation setups are made, to test the results of the simulation.

Remanufacturing is the industrial process of returning used products(cores) to a like-new or better condition. During this industrial process, the cores go through several process steps, e.g., inspection, disassembly, cleaning, reprocess (repairs), storage, reassembly and final testing. Manufacturing companies also see remanufacturing as a way to become more circular and sustainable in economic, environmental and social terms. Technological advancements within the robot industry have increased the possibilities for using more automation within there manufacturing industry, while recently, the remanufacturing of electric and electronic equipment (EEE) has grown around the world. This paper aims to identify the automation potentials of the remanufacturing of EEE. A multiple case study at four EEE remanufacturing companies was conducted to meet this aim. The case study, along with previous research, shows examples of EEE remanufacturing steps that are mainly performed manually. The results from this research show the possible automation potential for the process steps of cleaning, disassembly and reassembly at the four remanufacturing case companies.

About eighty percent of all engineering work done today is repetitive, and about ninety percent of all engineering work consist of modelling minor changes. By replacing all the repetitive human engineering work with computers, the engineers could instead focus on creating new products or improving the existing. This could make companies more competitive and increase sales. Using design automation to model small changes would also enable companies to produce small batches at a lower cost.

This project is done in collaboration with Thule Group. One of Thule’s largest product categories contain roof racks. The company manufacture the roof racks at their warehouse in Sweden and all variant modelling of them are performed by their technicians and engineers. For every new car model that is released, a new variant of the attachment for the roof racks needs to be modelled. There are different types of brackets used in the attachments, whereas two of them are called Evo Clamp and Evo Flush. For each new car model, new tool inserts for the manufacturing of the brackets also needs to be modelled. In previous research, a design automation process of the tool inserts for Evo Clamp was created. This project aims to use the outcome from that research to create a new design automation process for tool inserts to create Evo Flush.

To execute the project, the DRM framework was used. To gather information, a literature study and an empirical study were performed. Furthermore, the design automation was created using VB.NET and Solidworks. To evaluate the outcome of the project, three factors were set up to test the process by. The outcome from this project was also compared to the outcome from the Evo Clamp research.

The results showed that it was difficult to reuse and adapt the previous research since the templates for the tool inserts of the two different brackets were modelled in two completely different ways. Therefore, the main conclusion from this project is that; if the intention is to automate a process, then this must be kept in mind when modelling the components and templates. To have concrete modelling guidelines seems to be even more important if the intention is to reuse code from one process when automating another.

Customized products are becoming increasingly common, and increasingly important for maintaining a competitive advantage in certain industries. Being able to quickly and accurately respond to unique customer requirements can provide a competitive edge or even be the only path to survival. In practice, configurators are commonly used to manage the customization process, gathering the customer’s requirements and suggesting feasible solutions to the customer’s problem.

Fostering and maintaining a viable product customization offering is not easy. A particularly challenging category of products is one where an extensive engineering effort might be needed to even produce a reliable estimate of the product’s price. These products are usually referred to as engineer-to-order (ETO) products.

Prior work has pointed out the potential of using optimization as part of configuration solutions for ETO products, but the literature is limited in its extent and does not clearly prescribe how to structure and approach such solutions.

This thesis outlines a conceptual and technical architecture for implementing optimization-based configuration solutions. Reusable primitives for supporting the routines involved in this architecture are provided. These findings are verified through application and evaluation within two industrial case studies, also yielding important industrial needs to cover in the future research and development of the proposed framework. By examining three additional case studies, common issues in the development and deployment of design automation (DA) systems are identified.

Successful implementation of the proposed framework for optimization-based configurators can lead to two main benefits. First, engineering configurator prototypes can be developed rapidly, to test the viability of configurator projects – a category of projects prone to expensive failures. Second, optimization-based configurators can be used to support rapid design space exploration in early product development stages, leading to enhanced product knowledge in a critical phase, and in turn, increased product value.

This paper proposes an optimization framework based on the OpenMDAO software library intended for engineer-to-order products and applies it to the conceptual design of a Mobile Miner. A Mobile Miner is a complex machine and a flexible alternative to Tunnel Boring Machines for small-scale tunneling and mining applications. The proposed framework is intended for use in early design and quotation stages with the objective to get fast estimates of important product characteristics, such as excavation rate and cutter lifetime. The ability to respond fast to customer requests is vital when offering customized products for specific applications and thereby to stay competitive on the global market. This is true for most engineer-to-order products and especially for mining equipment where each construction project is unique with different tunnel geometries and rock properties. The presented framework is applied to a specific use-case where the design of the miner's cutter wheel is in focus and a set of Pareto optimal designs are obtained. Furthermore, the framework extends the capabilities of OpenMDAO by including support for mixed-variable formulations and it supports an exploratory approach to design optimization.

In order to efficiently design and deliver customized products, it is crucial that the process of translating customer needs to engineering characteristics and into unique products is smooth and without any misinterpretations. The paper proposes a method that combines design optimization with value-driven design to support and automate configuration of customized products. The proposed framework is applied to a case example with spiral staircases, a product that is uniquely configured for each customer from a set of both standard and customized components; a process that is complex, iterative and error-prone. In the case example, the optimization and value-driven design models are used to automate and speed-up the process of delivering quotations and design proposals that could be judged based on both engineering characteristics as well as their added value, thereby increasing the knowledge at the sales stage. Finally, a multi-objective optimization algorithm is employed to generate a set of Pareto-optimal solutions that contain four clusters of solutions that dominate the baseline design. Hence the decision-maker is given a set of optimal solutions to choose from when balancing different economical and technical characteristics.

This paper presents five industrial cases where design automation (DA) systems supported by design optimization has been developed, and aims to summarize the lesson learned and identify needs for future development of such projects. By mapping the challenges during development and deployment of the systems, common issues were found in technical areas such as model integration and organizational areas such as knowledge transfer. The latter can be seen as a two-layered design paradox; one for the product that the DA system is developed for, and one for the development of the DA system.

This paper describes a methodology for automation of measurements in Computer-Aided Design (CAD) software by enabling the use of supervised learning algorithms. The paper presents a proof of concept of how dimensions are placed automatically in the drawing at predicted positions. The framework consists of two trained neural networks and a rule-based system. Four steps compound the methodology. 1. Create a data set of labeled images for training a pre-built convolutional neural network (YOLOv5) using CAD automatic procedures. 2. Train the model to make predictions on 2D drawing imagery, identifying their relevant features. 3. Reuse the information extracted from YOLOv5 in a new neural network to produce measurement data. The output of this model is a matrix containing measurement location and size data. 4. Convert the final data output into actual measurements of an unseen geometry using a rule-based system for automatic dimension generation. Although the rule-based system is highly dependent on the problem and the CAD software, both supervised learning models exhibit high performance and reusability. Future work aims to make the framework suitable for more complex products. The methodology presented is promising and shows potential for minimizing human resources in repetitive CAD work, particularly in the task of creating engineering drawings.

Fixture layout is a complex task that significantly impacts manufacturing costs and requires the expertise of well-trained engineers. While most research approaches to automating the fixture layout process use optimization or rule-based frameworks, this paper presents a novel approach using supervised learning. The proposed framework replicates the 3-2-1 locating principle to layout fixtures for sheet metal designs. This principle ensures the correct fixing of an object by restricting its degrees of freedom. One main novelty of the proposed framework is the use of topographic maps generated from sheet metal design data as input for a convolutional neural network (CNN). These maps are created by projecting the geometry onto a plane and converting the Z coordinate into gray-scale pixel values. The framework is also novel in its ability to reuse knowledge about fixturing to lay out new workpieces and in its integration with a CAD environment as an add-in. The results of the hyperparameter-tuned CNN for regression show high accuracy and fast convergence, demonstrating the usability of the model for industrial applications. The framework was first tested using automotive b-pillar designs and was found to have high accuracy (approximate to 100%) in classifying these designs. The proposed framework offers a promising approach for automating the complex task of fixture layout in sheet metal design.

Introduction: Digitization is a crucial step towards achieving automation in production quality control for mechanical products. Engineering drawings are essential carriers of information for production, but their complexity poses a challenge for computer vision. To enable automated quality control, seamless data transfer between analog drawings and CAD/CAM software is necessary.

Methods: This paper focuses on autonomous text detection and recognition in engineering drawings. The methodology is divided into five stages. First, image processing techniques are used to classify and identify key elements in the drawing. The output is divided into three elements: information blocks and tables, feature control frames, and the rest of the image. For each element, an OCR pipeline is proposed. The last stage is output generation of the information in table format.

Results: The proposed tool, called eDOCr, achieved a precision and recall of 90% in detection, an F1-score of 94% in recognition, and a character error rate of 8%. The tool enables seamless integration between engineering drawings and quality control.

Discussion: Most OCR algorithms have limitations when applied to mechanical drawings due to their inherent complexity, including measurements, orientation, tolerances, and special symbols such as geometric dimensioning and tolerancing (GD&T). The eDOCr tool overcomes these limitations and provides a solution for automated quality control.

Conclusion: The eDOCr tool provides an effective solution for automated text detection and recognition in engineering drawings. The tool's success demonstrates that automated quality control for mechanical products can be achieved through digitization. The tool is shared with the research community through Github.

This project was conducted as a case study at Öhlins Racing AB, a manufacturer of suspension systems for automotive applications. Öhlins usually manufacture their components by traditional methods such as forging, casting, and machining. The project aimed to investigate how applicable Additive Manufacturing (AM) is to manufacture products for suspension systems to add value to suspension system components. For this, a proof of concept was designed and manufactured. The thesis was conducted at Öhlins in Upplands Väsby via the consultant firm Combitech. 

A product catalog was searched, screened, and one part was selected. The selected part was used as a benchmark when a new part was designed for AM, using methods including Topology Optimization (TO) and Design for Additive Manufacturing (DfAM). Product requirements for the chosen part were to reduce weight, add functions, or add value in other ways. 

Methods used throughout the project were based on traditional product development and DfAM, and consisted of three steps: Product Screening, Concept Development, and Part Design. The re-designed part is ready to be manufactured in titanium by L-PBF at Amexci in Karlskoga. 

The thesis result shows that at least one of Öhlin's components in their product portfolio is suitable to be chosen, re-designed, and manufactured by AM. It is also shown that value can be added to the product by increased performance, in this case mainly by weight reduction. The finished product is a fork bottom, designed with hollow structures, and is ready to print by L-PBF in a titanium alloy.