This paper investigates commuter transportation choices in Linköping, Sweden, to inform the design of sustainable and user-friendly solutions. The study uses interviews, observations, and travel diaries to understand factors influencing mode selection, revealing a prevalence of car usage and significant challenges with public transport. Based on this analysis, three commuter personas were developed. Student groups then used these personas to generate design solutions aimed at lowering barriers to public transport adoption and incentivizing its use.  

Robot safety standards defines Collaborative Operation as a state in which purposely designed robots work in direct cooperation with a human within a defined workspace. That is, an operator and an industrial robot complete assembly tasks at the collaborative workspace. A prerequisite to ensuring safety during all phases of operation is an understanding of the nature of hazards pertinent to collaborative systems. An automotive assembly station, where plastic panels are assembled on a continuously moving line, formed the basis for research operations meant to understand safety issues when a large industrial robot aids an operator in assembly tasks. This led to the development of a laboratory demonstrator whose design and functioning will be presented in this article. Additionally, the hazards identified during risk assessment along with measures to mitigate the associated risks will be presented in order to highlight the nature of hazards pertinent to collaborative systems.

Activities to support manufacturing research are carried out with the intention to gain knowledge of industrial problems and provide solutions that addresses these issues. In order for solution to be viable to the industry, research activities are carried out in close collaboration with participants from the industry, academia and research institutions. Interactive research approach motivates participants with multi-disciplinary perspective to collaborate and emphasizes joint learning in the change process. This article, presents a methodology, where participants with different expertise can collaborate to develop safety solutions. The concept of a demonstrator, which represents cumulative result of a series of research activities, is presented as a tool to showcase functioning and design intent in a collaborative research environment. The results of a pilot study, where manufacturing professionals evaluated design decisions that resulted in a demonstrator, will be presented. (C) 2018 The Authors. Published by Elsevier B.V.

The main objective of a reliability study should always be to provide information as a basis for decisions, e.g. concept choice, design requirements, investment, choice of suppliers, design changes or guaranty claims. The choice of reliability method depends on the time allocated for the reliability study, the design stage, the problem at hand and the competence and resources available.

During a reliability study the engineer focuses on providing a graphical means of evaluating the relationships between different parts of the system, gathering or assessing the reliability data for the components and interpreting the results of the analyses. Even though the commercial software tools available claim to provide answers to most reliability questions, choosing which method is best suited is not an easy task. Often several methods can be applied and none of them will fit the purpose perfectly.

This paper presents a guideline for choosing the best suited reliability method in early design phases from two aspects: objective and system characteristics. The methods studied are the most common methods available in commercial software tools: Reliability Block Diagram (RBD), Fault Tree (FT), Event Tree (ET), Markov Analysis (MA) and Stochastic Petri Network (SPN). The guideline considers two aspects: the characteristics of the system studied and the scope of the analysis. The applicability of each of the five chosen methods is assessed for all possible combinations of system characteristics and objective. A study has been made at Saab Aeronautics to evaluate the practical use of the analysed methods and how this guideline can improve the selection of appropriate reliability methods in early design phases.

When developing a safety critical system, there are many aspects that need to be balanced against each other in order to reach an optimal design such as safety requirements, reliability goal, performance specifications and budget constraints. In an early design stage, it is vital to be able to screen the design space for a set of promising design alternatives for further studies. This paper proposes an approach capable of investigating the trade-offs described above, combining the techniques for system safety and reliability analysis with optimization methods. Markov analysis is employed for modeling the system safety and reliability characteristics and a Genetic Algorithm is used for optimization. The proposed method is applied to the design of an electric supply system for an aircraft, involving selection of components from different suppliers. First a model is built for each objective, i.e. cost, safety, and reliability. The models are validated and optimization is performed. The obtained result is the selection of suppliers for each component in the system in order to achieve a balance between system safety, reliability, and other design objectives.

ldentifying and attending to faults and shortcomings in the design before it reaches the market is crucial in order to achieve a profitable product. Letting the customer detect the shortcomings in the design is not an acceptable approach today, and will inevitably lead to unsatisfied costumers. Activities aimed at identifying faults in the product may becarried out during the entire design process, but faults identified late in the design process will require more resources to put right, and may affect the performance negatively to a higher degree than faults identified upstream in the process. This article aims to develop the theory and methodology regarding identification of potential failures in a system upstream from the design process. The result presented in this article comprises a method for modelling failuresand a process for identirying potential failures in conceptual solutions. The result is based onqualitative system modelling, where the known physical phenomena are compared to the system in order to evaluate the potential of different behaviour occurring. The effects the behaviour emits determine its impact on the system, and thus the potential for a failure. The article concludes with a comprehensive example demonstrating, and to some extend verirying, the method of identifying potential failures.

This dissertation embraces the issue of evaluating design concepts. Being able to sort out the potential“best solutions” from a set of solutions is a central and important part of the design process. The subjectdiscussed in this dissertation has its origins in the lack of knowledge about design concepts, somethingwhich is characteristic of the initial part of the design process and which frequently causes problems whenit comes to evaluation and selection of solutions. The purpose of this dissertation is to develop aids andmethods that enhance the understanding of design concepts in the early phases of the design process.

From deductive reasoning about the fundamental mechanisms of the evaluation activity, the work hasbeen divided into three different areas: process and system modelling, concept optimisation, andidentification of potential failures.

The bearing of the work within the area of process and system modelling has a verifying character. Theobjective of the work has been to analyse how established design methodology, which has its commonapplications within traditional engineering industry, may be applied within an area that is characterised bymore multidisciplinary interfaces, like biotechnology. The result of a number of case studies, in whichdifferent types of biotechnical systems where analysed and modelled, shows that the methodology isapplicable even for biotechnical products. During the work the methodology has also been furtherelaborated on in order to better suit the distinguishing characteristics exhibited in the development ofbiotechnical systems.

Within the area of concept optimisation, an approach for optimising the concept generation has beenelaborated. By formalising the step in both concept generation and evaluation, it has been possible toapply genetic algorithms in order to optimise the process. The work has resulted in a model thatautomatically creates and sorts out a number of potential solutions from a defined solution space and adefined set of goals.

The last area, which deals with identification of potential failures, has resulted in a rather novel way toconsider and model the behaviour of a system. The approach is an elaboration of the modellingtechniques within system theory, and deduces the system’s behaviour from known physical phenomenaand the system’s ability to effectuate them. The way the different behaviours interact with one another, byaffecting the properties of the system, determines the potential for a failure to occur. A “failure”,according to the model, is described as an unintended behaviour which obstructs the system’sfunctionality, i.e. which affects the conditions of a desired behaviour.

The dissertation has resulted in three different means for approaching the difficulties associated with theevaluation of design concepts. The means are applicable during different parts of the design process, butthey all address the same issue, viz. to enhance the understanding of the design solutions.

Four complex biotechnology products/product systems (a protein purification system, a bioreactor system, a surface plasmon resonance biosensor, and an enzymatic glucose analyzer) are analyzed using conceptual design principles. A design model well-known in mechanical system design, the Hubka-Eder (HE) model, is adapted to biotechnology products that exemplify combined technical systems of mechanical, electronic, and biological components, here referred to as bio-mechatronic systems. The analysis concludes that an extension of the previous HE model with a separate biological systems entity significantly contributes to facilitating the functional and systematic analyses of bio-mechatronic systems.

Decisions made during the conceptual phase of the design process are crucial for long-term economic success. The correction of late-identified failure is often both difficult and time consuming, and may have a negative effect on performance. In the prevalent design methodologies, there are shortages concerning systematic and objective methods to evaluate solutions with respect to weak spots and errors, especially early in the design process. The objective of this article is to strengthen the evaluation methodology by examining the possibilities to identify potential problems within conceptual solutions, and to develop a means that facilitates the evaluation regarding this matter. The results presented in this article may be divided into two parts: a descriptive part where a generic approach of modelling the failure behaviour is proposed and a prescriptive part where a foundation of a methodology for identification of potential failure is outlined.

Process analyties. technology (PAT) and mechanical design science are interconnected. This article describes how a well-established design modelling approach. The Hubka-Eder model, is applied to the concepis of PAT end quality by design (QBD). The model connects PAT With quality management concepts as defined for PAT by lhe ICH guldelines for quaiity issues. Examples are taken fom biopharmaceutical applications. but lhese are also applicable to other pharmaceutical ingredients (API). Benefits of using a conceptual design modelling approach on PAT and related subjects are discussed and suggestecl as a complementary functionality analysis tool in PAT and quality design pharmaceutical processes.