In the era of Industry 4.0 and digitalization, planning solutions need to co-exist with each other and be able to manage higher complexity and with a higher performance. As the concept smart production planning and control is a part of industry 4.0, it is highly relevant to study and is in this paper explored on the four elements of smart PPC (real-time data management, dynamic production planning and re-planning, autonomous production control, and continuous learning). This paper provides a framework for linking the four elements of smart PPC with data quality issues in state-of-the-art production planning and control environments. Maintaining a high standard of data quality in the business processes aids the organization to stay competitive in its market. Hence, our assumption is that a high level of data quality is needed in production planning and control for a high-performance outcome. The empirical part of our study results in a bar-chart of seven data quality problems and their occurrences together with their causes in PPC. According to the empirical data results, inaccurate data entries is the most common data quality problem related to PPC. The causes of the inaccurate data entries can be linked to human resources and organizational control. Future research should strengthen the validity of the proposed linkages between data quality problems and elements of smart PPC and implications on strategic, tactical, and operational planning levels.

In this paper, construction material supplier and construction site performance are assessed according to the supply chain operations reference (SCOR) model. Current applicable literature focuses mainly on assessing the main contractor’s ability to construct a building according to customer requirements, i.e. construction performance. Omitting supplier performance when evaluating construction performance reduces the ability to improve the construction supply chain, as reasons for cost and time overruns and quality deficiencies will often be overlooked. In this paper, the SCOR metrics perfect order fulfilment (POF), source cycle time (SCT) and cost to source(CS) are measured to assess construction supplier reliability and construction site responsiveness. The values for POF, SCT and CS are measured to be 38%, 134 min and EUR 249, respectively. The practical implications are summarised in five improvement suggestions concerning communication, predefined material allocation, supplier performance assessment, delivery verification and notification and use of the SCOR model.

In recent years, attention has been placed on the logistics activities in construction projects in order to reduce total costs. The construction industry is experiencing poor productivity, resulting from an inability of contractors, subcontractors, and suppliers to cooperate efficiently. Research on logistics in construction lacks a holistic perspective and tends to focus on one activity at a time. This research presents the Builder’s SCOR model (BSCOR) to be used for logistics improvements in construction. The model is based on the Supply Chain Operations Reference Model (SCOR model) covering the total supply chain. The BSCOR model is empirically derived through five case studies at different construction sites over a period of five years. This has resulted in a model covering the activities Source, Build, and Plan, that describes the flow of materials to and on the site and how ownership passes to the client. With the BSCOR model, contractors can map the material and information flows between supply chain members with standardized process definitions. It is also possible to precisely measure the supply chain performance and to know where to put improvements efforts. The main intention with the BSCOR model is to help the industry reduce costs and increase productivity.

The purpose is to analyse how supply chain planningin construction can be better coordinated, both concerning the supply chain assuch and concerning activities on-site. A literature review and a case studyidentify a number of problems that occur due to poor coordination. To mitigatethese problems it is suggested that a structured framework, like the SupplyChain Operations Reference (SCOR) model, can facilitate the implementation ofsupply chain management so as to enhance coordination and supply chainperformance in the construction industry. The use of a structured model isargued to improve the integration of subcontractors and suppliers in the maincontractor’s planning process. The focus is on the so called “Plan” process in theSCOR model, which is the process that is used to coordinate supply chainactivities in all parts of the supply chain, including site activities. Thefindings identify which parts of the SCOR Plan process that need to be adjustedto fit the construction industry and how it can facilitate the synchronisationbetween the main contractor and its subcontractors. The main contribution is thedevelopment of a model for mapping and managing the construction planning process,so as to enhance coordination and the performance of the construction supplychain.

Non-sustainable transportation is a great part of the stress that human activities put on the environment. Transportation of construction material are today performed all but exclusively by road, a mode that is cheap and fast, but at the same time heavy on emissions. In light of this, the effects of a modal change from road to combined road/rail transportation are studied from the viewpoint of a case company producing prefabricated concrete units. The study includes economic and environmental as well as operational effects. A case study is performed at the producing company by looking at actual invoices and delivery orders for the present mode of transportations. To assess the present operations, an intermodal alternative was created and studied. The comparison clearly shows that the environmental impact of the intermodal transportation is only a fraction of that of the road transportation. However, intermodal transportation is less cost efficient, flexible and reliable. The results imply the construction industry as a whole could lessen its environmental impact by employing intermodal transportation, however, without changes in regulations and policies to negate the economic disadvantage, intermodal transportation in its current state will not be a viable option for the studied company.

Since 2009, Linköping University has been running the Builder’s SCOR project. The project is supported by the research collaboration Brains&Bricks where Linköping University, the construction company Peab, and the municipality of Katrineholm participates to enhance the efficiency of the construction industry. The Builder’s SCOR model (BSCOR) is based on the SCOR model (Supply Chain Operations Reference Model) developed and supported by Supply Chain Council (SCC, 2012, SCOR, 2010). The BSCOR project is divided into several sub-projects and is still on-going. This paper reports on the third phase in the project where the Make-process of SCOR is converted to BSCOR in terms of process definitions. The first phase, the pilot study, used the SCOR model in a construction setting and evaluated how useful the model was. This work is reported in Johansson and Persson (2011) and Persson et al. (2009), where the need for something very similar to the BSCOR model is argued. The second phase included a case study of a mid-range construction project (turnover of € 1 – 10 million) where the SCOR-processes Source and Deliver were studied. This resulted in new definitions of processes and metrics in order to take the unique conditions of the construction industry into consideration. The work is reported in Persson and Thunberg (2012) and Thunberg (2011). The third phase, in this paper, studies the Make-processes in construction through two case studies of midrange construction projects. This paper outlines the results of the case studies and defines the processes in Make at the three different levels of BSCOR. As the last phase, Deliver and Plan will be studied through interviews with personnel from construction companies as well as from companies that order and buy construction projects. A study on adapting the Return-process is not conducted as the results from Thunberg (2011) indicate that faulty construction materials are seldom returned. With the four phases outlined here, a complete BSCOR model will be defined and used in several construction projects. The aim is to broaden the scope of use to other construction companies outside the collaboration of Brains&Bricks.

Purpose

The purpose of this paper is to improve construction logistics by introducing an adapted version of the SCOR (Supply Chain Operations and Reference) model. Sub-processes and metrics related to the Deliver and Source processes in the SCOR model that are in need of changes to adapt SCOR to the construction industry settings are identified.

Design/methodology/approach

By observing the Deliver and Source processes and metrics in the SCOR model at a construction site, suggestions for important changes that need to be made to the SCOR model are given. This is done by using case study as a research method for theory building.

Findings

Findings from the case study result in proposals for new Deliver and Source  sub-processes, changes in current sub-processes and new metrics. These changes constitute the first version of the Builder’s SCOR model (BSCOR).

Research limitations/implications

This paper presents the work of finding important changes related to the main processes Deliver (delivery of materials from supplier to site) and Source (receiving materials at site) in the SCOR model. Future work will consider important changes related to the main processes Make, Deliver (from site to customer), Plan and Return.

Originality/value

This paper analyses which parts of the SCOR model that need (or not need) to be adapted to embrace construction industry settings, resulting in a draft of a model based on the SCOR model that comprehends construction industry settings. Accordingly, this can lead to a better adaption of the processes and metrics to map, control, and coordinate the supply chain which can result in an increased profit for construction companies.

Supply Chain Simulation (SCS) is today a well-defined branch of discrete-event simulation applications. The differences between different applications are usually small, but in the case of SCS, models tend to be larger, take longer time to build and are harder to validate. To remedy some of these issues in SCS, we propose to use the SCOR model (Supply Chain Operations Reference Model) as a tool to speed up the simulation modeling of supply chains. The SCOR model can be useful in the conceptual phase, the modeling phase, and in the experimental phase of a simulation project. In SCOR Template, a modeling template in Arena, all level 3 processes of Source, Make, and Deliver are modeled to provide the SCS model builder a tool that is fast, follows the SCOR standards in processes and metrics, and simple to use. Here we report on the third version of the SCOR Template.

In this study the possibilities of a modal shift from road to intermodal transportation for a Swedish company producing concrete units is investigated, for the purpose of determining the economic and environmental (limited to CO2-emissions) effects such a shift would bring. The study is relevant since the case company is interested in moving their transports from the roads, and the European Union has promoted a modal shift away from road transportation to more sustainable modes.

The present day transportation, along with three plausible different intermodal transportation scenarios are analysed. The first scenario incorporates a crane-equipped truck that loads the train near the production facility, and then travels with the last load carrier to the destination, concurrently with the train, to repeat the operations in reverse order at the receiving end. The second scenario employs rail cars that can load entire trucks, including their cargo. In the third scenario, the cargo is transhipped from road to rail at terminals operated by a logistics provider.

All three intermodal scenarios reports higher costs than for road transportation, not only because of what is believed to be a too short door-to-door distance, but also due to high drayage costs. However, the environmental impact is heavily reduced for all three scenarios, in one by as much as 42%. These results contribute to the academic knowledge base of factors influencing the break even distance for intermodal transportation, and also to policy makers and practitioners in the way that the immense difference in environmental impact might be something worth to invest both time and funds in.