With the increased electrification of transportation, there is a growth in the number of electric vehicles (EV) in use, and hence also discarded EV batteries. It is critical to trace the batteries so that the policy of electrification does not lead to a negative impact on sustainability. To achieve the goals of circular economy, it is necessary to consider the sustainable extended life cycle strategies of reduce, reuse and recycle. Information gathering and sharing through the supply chain is the key driver for enabling the tracking and tracing of materials and services needed. Traceability indicators across the value chain may enable the creation of a comprehensive database that aids the circular economy goals. In this study, we discuss three different circular economy business models and identify the key traceability indicators for enabling circularity in the lithium-ion battery application in the automotive sector. Insights are used to develop a framework for viable EV battery circularity, capturing three key circular economy elements and four traceability characteristics for different circularity types.

Visibility across supply chains has been a key concern for organisations for many years, but the tools and information systems to achieve real-time visibility have not been available until recently. In response to uncertainty and complexity, advanced information and communication technologies have been explored for supply chain visibility (SCV). However, managerial perspectives are largely absent from the current literature. In response, this paper systematically documents managerial factors influencing SCV and information that should be collected and shared among supply chain partners for better visibility. A multi-stage Delphi analysis was conducted with 26 supply chain experts from various globally recognised enterprises with manufacturing units located worldwide. The results provide details on prioritised managerial perspectives and experiences within (1) factors affecting SCV (drivers, enablers, challenges and contingencies), (2) SCV content (supplier, internal and customer information) and (3) implications of SCV (capabilities and performance effects). One observation was that forecasting is not deemed as important due to severe disruptions in supply chains. Real-time visibility for better predictability emerged as the top priority. This study is among the few that empirically explores factors influencing supply chain visibility and generates new insights into why barriers can be difficult to overcome in complex supply chain settings.

Visibility in production logistics and across the supply chain has become a key concern for organizations. Its need has been further emphasized due to the current COVID 19 crisis. Organizations find it challenging to prepare the internal logistics and supply chain, and quickly respond to such unexpected events, due to low visibility. Against this backdrop, the paper, which is a work-in-progress, systematically documents different factors influencing supply chain visibility and crucial information that should be collected and shared among supply chain partners for better visibility. A Delphi analysis is being conducted with twenty-six supply chain experts from various globally recognized enterprises with manufacturing units located worldwide. The study starts with a short open-ended questioner to collect a comprehensive list of antecedents, drivers, barriers, effects, and visibility information based on the qualitative response from the experts. The preliminary results from the first round of the Delphi analysis indicate that risk management, environmental sustainability, and supply chain control are some of the key drivers. Lack of IT infrastructure and maturity are some of the barriers, integrated systems, and technology maturity are among the key antecedents and gaining planning capability and better customer service are some of the positive effects of supply chain visibility as per the experts’ opinion. In addition, information related to planning, supplier location, and deviation are among the crucial ones that require the collection and sharing for better supply chain visibility. This research study is among the few that empirically explores factors influencing supply chain visibility and generates new insights as to why the barriers can be difficult to overcome in complex supply chain settings.

There is a trend in industries towards adoption of new technologies coming from Industry 4.0 to improve logistics operations. This has also led to new requirements on engineering education. This paper presents work in progress on a mixed reality game that is intended to be used for the education on engineers and engineering students in the blended lab environments. The game itself consist of a physical and a digital component, and the focus in this article is to describe the design and prototypical implementation of the physical part and how that can be operated in a remote lab environment.

In recent years, policy makers as well as urban logistics and transport research have investigated how to reduce environmental impact from transportation in urban areas. Therefore, many new frameworks that can help a specific actor in its decision making process at a certain decision making level (i.e., business or policy level) have been implemented and published. However, the first screening of existing literature did not reveal frameworks that can be used across different decision making levels. This limits the possibility for actors using the same infrastructure but not necessarily co-operate to discuss how the actions and needs of each actor of different decision making levels mutually influence each other. This paper first presents an outcome of a literature review and analysis of existing research project results before. It combines these to a multi-layer framework that can enhance collaborative decision-making and seamless aggregation of performance measures such as environmental impact from multiple transportation activities in and around urban areas. For this multi-layer framework, factors are identified, and possible relationships across the various layers are indicated. The field of application is the area near urban manufacturing sites and specifically addressing all actors that share on regulate infrastructure relevant to last mile inbound logistics. The source of data is project databases as well as for the literature review research databases. The methodology applied is a combination of a literature review based on database entries and a snowball approach. The article also presents how the framework can be prototypically implemented in participatory simulations using a simplified example. Potential usage for establishing holistic urban mobility structures is also discussed.

Practical lab exercises and haptic games are often used to create understanding and awareness of how technologies can support the quality of warehouse operations. However, not all students have access to a suitable physical lab or game environment. A Mixed reality sandbox mode was planned, a game mode of free form that emphasises freedom of movement and offers the player a lot of flexibility and ingenuity in completing tasks and coming up with solutions to the game objectives with a combination of Augmented Reality and physical tools. The purpose of playing this game is to promote the importance of using sensors to increase the efficiency of inbound logistics remotely.

Designing Serious Games (SGs) is a complex process, often putting game play in a central role during the design process. Therefore, the game mechanics can create unwanted tangential outcomes. Further challenges emerge from the time constraints to deliver a purposeful product that meets the requirements of the target group, while maintaining a low budget. The re-use of game components and a participatory design may contribute to overcome these challenges. This paper presents and reports on a case study integrating reuse and re-purposing of a game-engine while involving the future users in the early phase of the design process.

Background: Serious games can be a powerful learning tool in higher education. However, the literature indicates that the learning outcome in a serious game depends on the facilitators' competencies. Although professional facilitators in commercial game-based training have undergone specific instruction, facilitators in higher education cannot rely on such formal instruction, as game facilitation is only an occasional part of their teaching activities. Objective: This study aimed to address the actual competencies of occasional game facilitators and their perceived competency deficits. Methods: Having many years of experience as professional and occasional facilitators, we (n=7) defined requirements for the occasional game facilitator using individual reflection and focus discussion. Based on these results, guided interviews were conducted with additional occasional game facilitators (n=4) to check and extend the requirements. Finally, a group of occasional game facilitators (n=30) answered an online questionnaire based on the results of the requirement analysis and existing competency models. Results: Our review produced the following questions: Which competencies are needed by facilitators and what are their training needs? What do current training courses for occasional game facilitators in higher education look like? How do the competencies of occasional game facilitators differ from other competencies required in higher education? The key findings of our analysis are that a mix of managerial and technical competencies is required for facilitating serious games in higher educational contexts. Further, there is a limited or no general competence model for game facilitators, and casual game facilitators rarely undergo any specific, formal training. Conclusions: The results identified the competencies that game facilitators require and a demand for specific formal training. Thus, the study contributes to the further development of a competency model for game facilitators and enhances the efficiency of serious games.

A main challenge for teachers is to provide good educational offers that appear both appealing as well as motivating to students to learn about the content according to the curriculum. Educational games are thought to be a good complementary way of provide this learning environment, but, so far, the adaption of educational games to a specific context is not only costly but also requiring a lot of knowledge related to game design. This article provides some examples on how gamified lessons paths can be changed in a simple way and how different components can be re-used, in order to save costs and time and to improve the overall quality of the learning experience.

The role of the teacher is to help students improve their knowledge and skills. While it is acknowledged that learning occurs within specific activities and contexts, the adaptation of learning settings to distinct didactical objectives and learner needs remains a challenge. Under these premises, the authors explore the demanding endeavour of creating and tailoring game-based learning activities for specific subjects. The design and personalisation of rich media applications require an extra effort on the teacher side and imply advanced skills. The paper explores the opportunity to reuse gamified lesson plans using an authoring pipeline that reunited authoring tools, game narratives and minigames.

The popularity of location-based games continues unabated and is benefiting from the increasing use of mobile end devices and advantageous general conditions, such as the Internet of Things and the Smart City paradigm. This enormous potential of engagement should also be tapped for serious location-based games, i.e. the use of location-based games beyond the purpose of entertainment. The workshop “Applying and Facilitating Serious Location-based Games” aims to contribute to the development of this potential. In the article, the theoretical basis for this workshop is derived and corresponding frameworks are presented.

Nowadays, digital twins exist everywhere in various fields. However, an analysis of existing applications in manufacturing and logistics revealed that many entirely apply the concept. To identify when a complete implementation of the concept is beneficial, we analyse the need and the implications within production logistics. This study also presents an architecture supporting integrating a digital twin into production logistics and a corresponding application scenario. Based on this, we have derived practical applications. Each application is applied to different situations, and actual benefits can overcome the limitations of the previous studies. 

The issue of national and European identity is driving many of the issues that are currently of concern to European citizens. The Erasmus+ funded RU EU? project aims to develop an innovative online game, the RU EU? game, that will help students across Europe to develop a better understanding of their own National and European identity and values, as well as those of others, and to challenge them about their attitudes and prejudices by tackling problem solving dilemmas relating to identity. It is hoped that the game will provide an engaging platform for young Europeans to confront some of the complex and confusing issues surrounding National and European identity at a time of change and increasing tension across Europe. This paper describes the early stages of the game design and focuses on characterizing the learning outcomes and game mechanics for the RU EU? game and bringing these together.

The Swedish strategic innovation programme, Produktion2030, is a national long-term effort towards global industrial competitiveness addressing Swedish industry’s transition towards climate goals of the European Green Deal while simultaneously realising smart manufacturing and Industry 4.0 (I4.0). This paper investigated the extent of sustainability implementation and implications of I4.0 technologies through a nation-wide quantitative survey in Produktion2030’s 113 collaborative research projects. The analysis showed that 71% of the assessed projects included environmental aspects, 60% social aspects, and 45% Circular Economy (CE) aspects. Further, 65% of the projects implemented I4.0 technologies to increase overall sustainability. The survey results were compared with literature to understand how I4.0 opportunities helped derive sustainability and CE benefits. This detailed mapping of the results along with eight semi-structured interviews revealed that a majority of the projects implemented I4.0 technologies to improve resource efficiency, reduce waste in operations and incorporate CE practices in business models. The results also showed that Swedish manufacturing is progressing in the right direction of sustainability transition by deriving key resilience capabilities from I4.0-based enablers. Industries should actively adopt these capabilities to address the increasingly challenging and unpredictable sustainability issues arising in the world and for a successful transition towards sustainable manufacturing in a digital future.

This paper proposes a conceptual implementation model for small and medium enterprises (SMEs) to follow as part of their digitalization implementation. It can later be translated into a practical step by step guide for SMEs to practice during their digital transformation. The model is based on gradually developing industrial capabilities that can influence production processes performance. The model development was based on a critical literature review and a real case industry application. The case data served as direct feedback to the model to assess both the model validity and the actual SMEs needs. The capabilities included in the model are proved to directly influence the performance positively. In comparison with existing models and frameworks, this model envisions the company a full digital shift by proposing an achievable sequence which SMEs in a resource-efficient way could start deploying in compliance with their business needs. SMEs can utilize the capabilities as a foundation for a system that supports continuous improvement in the whole factory.

Nowadays, Industry 4.0 (I4.0) has become a trendy topic in manufacturing industries worldwide. The definition is far from being comprehensible for small players, and the practical uptake is ambiguous. Transnational companies are often at the top in deploying I4.0 features, learning primarily from their experimentation. Alternatively, small- to medium-sized enterprises (SMEs), given their less stable value chains and unsteady processes, tend to target most of their efforts on controlling disturbances and adopting solutions for deviation control. Such solutions can be features that set the path for SMEs to transition to I4.0. This paper aims to examine the reported degree of digitalization in implemented solutions in SMEs when handling deviations and analyze the integration of such solutions in their digital transformation process. Systematic literature review (SLR) is used to examine literature published up to and including January 2019. The results show a higher concentration on practical applications rather than on frameworks. Existing frameworks that focus on SMEs address particular elements of I4.0 rather than a gradual shift with a holistic view, increasing the deployment difficulty for SMEs. This paper identifies potential constraints in deployment if such a trend maintains for consecutive years.

In a time of change focusing on the application of technology, there is a high risk of underestimating the compliance of internal needs and adaption to context. The research study employs a qualitative approach using the case study methodology. The source of data comes from five different manufacturing companies categorized as Small to Medium Size Enterprises (SMEs). A multidisciplinary team performed semi-structured interviews and fieldwork at each site, along with regular online meetings with the partners. The study employs five dimensions of the information quality perspective to assess information utilized to support deviation handling and connects the information quality deficiencies to the digital tools' impact. The empirical findings indicate the need for the companies to perform a requirement analysis of information needs before the adoption of digital systems or digital tools, to assess their current state in terms of data and information. The paper discusses the impact digital tools may have on deviation management in SMEs and under which circumstances digital tools could improve deviation management. Lastly, this paper intends to shed light on the utilization of digital technologies for disturbance handling on the production shop floor.

In a time of change focusing on the application of technology, thereis a high risk of underestimating the compliance of internal needs and adaption to context. The research study employs a qualitative approach using the case study methodology. The source of data comes from five different manufacturing companies categorized as Small to Medium Size Enterprises (SMEs). A multi- disciplinary team performed semi-structured interviews and fieldwork at each site, along with regular online meetings with the partners. The study employs five dimensions of the information quality perspective to assess information utilized to support deviation handling and connects the information quality deficiencies to the digital tools’ impact. The empirical findings indicate the need for the companies to perform a requirement analysis of information needs before the adoption of digital systems or digital tools, to assess their current state in terms of data and information. The paper discusses the impact digital tools may have on deviation management in SMEs and under which circumstances digital tools could improve deviation management. Lastly, this paper intends to shed light on the utilization of digital technologies for disturbance handling on the production shop floor.

The paper analyses under which circumstances it is possible to develop efficient low- cost-solutions in a small manufacturing company and the impact the introduction of information technology has on developing managerial capabilities of industrial processes. It follows an exploratory single-case study research design. Data have been collected from direct observations, documents such as production orders and log sheets, and semi- structured interviews. It presents an implemented low-cost-solution for supporting an SME in its first two steps of the digitization process. The tool is adaptable and transferable to similar manufacturing companies suggesting that the start of the digitalization process can be heavily simplified.

The purpose of this study is to analyze the use of Simulation-Based Multi-Objective Optimization (SMO) for Reconfigurable Manufacturing System Configuration Analysis (RMS-CA). In doing so, this study addresses the need for efficiently performing RMS-CA with respect to the limited time for decision-making in the industry, and investigates one of the salient problems of RMS-CA: determining the minimum number of machines necessary to satisfy the demand. The study adopts an NSGA II optimization algorithm and presents two contributions to existing literature. Firstly, the study proposes a series of steps for the use of SMO for RMS-CA and shows how to simultaneously maximize production throughput, minimize lead time, and buffer size. Secondly, the study presents a qualitative comparison with the prior work in RMS-CA and the proposed use of SMO; it discusses the advantages and challenges of using SMO and provides critical insight for production engineers and managers responsible for production system configuration.

Augmented Reality (AR) provides an immersive experience platform where players may interact with the real world. Virtual digital information details enhance this interaction with the physical environment. This paper focuses on investigating using Augmented Reality (AR) technology for player’s interaction influences the game design (technical features and interactivity aspects mainly) that could facilitate its players to achieve its proposed Intended Learning Objectives when playing different scenarios for logistic operations. To achieve this, an initial mock-up is set up with simple AR interactions to analyse the overall immersive player’s experience.

There is an increasing trend to use digital and interactive tools in classrooms. There are different types of resources like serious games, gamified applications, learning platforms and many other means of interactive learning and educational tools that are being used in classrooms. However, it is quite challenging to engage students with certain impairments in this interactive learning, since the tools are often not designed for their needs. Therefore, there is a need to make design considerations flexible enough to accommodate specific requirements and needs that could influence the playing experiences for these groups. The paper explores and discusses design considerations of a digital learning environment. These are the initial design considerations with the focus on improving player experience. In this context, the emphasis is on engagement factors mainly that could support learning, keeping under consideration the target group of visually impaired students.

Developing IIoT-enabled digital services is essential for facilitating human centered digital transformation and achieving resource-efficient production. IIoT-enabled digital services focus on providing the best possible value proposition to end users based on three main components including hardware, middleware, and visualization applications. An area of increasing interest is that of developing IIoT-enabled digital services in smart production logistics (SPL) that facilitate the delivery of material and information in manufacturing. Prior studies focusing on IIoT-enabled digital services give precedence to the location, energy consumption, and execution of material handling tasks in SPL. However, the literature neglects the importance of supporting staff responsible for maintenance of material handling equipment. Recent publications propose the use of Maintenance Opportunity Windows (MOW), yet this approach requires extensive calculations unsuitable to the dynamic environments of manufacturing. Addressing this need, the purpose of this study is to propose IIoT-enabled digital services for detecting MOW in material handling for the automotive industry. This study presents two contributions. Firstly, we draw extant knowledge about IIoT architectures in SPL to a novel context, namely that of MOW. Accordingly, this result reduces the time and resources for acquiring, processing, and identifying empty spots in MOW as compared to prior studies. Secondly, the study proposes IIoT-enabled digital services in material handling targeting maintenance staff including finding, filtering, and detecting the status of forklifts and their MOW. In doing so, the results complement existing literature about SPL targeting the autonomous coordination and scheduling of material handling. This is critical for offering digital services supporting the working needs of maintenance staff for a human centric industrial transformation.

Digital Twin (DT)-based services including Industrial Internet of Things (IIoT) are essential for achieving the vision of Smart Production Logistics and enhancing manufacturing competitiveness. DT-based services combining IIoT provide real-time location of materials and optimization of resources for addressing mass customization and fluctuating market demand. However, literature applying IIoT and achieving DT-based services in Smart Production Logistics (SPL) is scarce. Accordingly, the purpose of this study is to analyze the combined use of DT-based services and IIoT in SPL. We propose a framework combining DT-based services and IIoT for the real-time location and optimization of material handling. The study draws results from an SPL demonstrator based on a case in the automotive industry applying the proposed framework. The results show improvement in the delivery, makespan, and distance travelled during material handling. The study provides critical insight for managers responsible for improving the delivery of materials and information inside a factory.

Digital servitization (DS) enabled by the Industrial Internet of Things (IIoT) is essential for securing long-term competitiveness in manufacturing. The literature identifies the need for developing data models for multichannel communications across IIoT devices that fulfil the DS vision. This is crucial for avoiding isolated systems based on proprietary solutions and for promoting data sharing and interoperability across existing and future DS applications. Accordingly, this study proposes a data model for multichannel communication that facilitates IIoT-enabled DS for smart production logistics (SPL). We present three findings from a case study focussing on material handling in a manufacturing company. First, this study provides a model with four modelling profiles, including IIoT devices, databases, and services for multichannel communication. Second, it shows how the proposed modelling profiles transfer information across monitoring, control, optimisation, and autonomous decision services. Third, it presents the operational benefits of applying the proposed data models, including improvements in the delivery, makespan, and energy of material handling. These findings are essential for capturing, processing, and transferring information across products, services, and software databases in IIoT-enabled DS for SPL. They are relevant for manufacturing managers and academics and improve our understanding of IIoT-enabled DS's deployment for SPL in manufacturing.

Combining Smart Production Logistics (SPL) and Machine Learning(ML) for adaptive scheduling and execution of material handling may be criticalfor enhancing manufacturing competitiveness. SPL and ML may help identify,adapt, and respond to scheduling changes originating from disturbances in andenhance the operational performance of material handling. However, the literaturecombining SPL and ML for material handling is scarce. Accordingly, thepurpose of this study is to propose a framework applying ML for the dynamicscheduling and execution of material handling tasks in SPL. The study proposesan architecture including Cyber Physical System (CPS) and Internet of Things(IoT) applying ML for the dynamic scheduling and execution of material handling.Then, we describe the ML inputs, interactions, and work flow for realizingthe proposed architecture. Finally, the study presents digital services in a simulationenvironment exemplifying the dynamic scheduling and execution ofmaterial handling in SPL. The study concludes with essential implications to themanufacturing industry.

This study addresses the need for empirical studies involving Cyber Physical Systems (CPS) in Smart Production Logistics (SPL). The study explores the challenges for generating, handling, and using real-time location information originating from CPS in SPL. We conduct an explorative case study at a multinational manufacturer developing a CPS for material handling. Drawing from SPL literature and organization theory, the results show how increased information processing capacity may reduce equivocality and uncertainty in SPL leading to active perception, response, and autonomous decision-making. The study presents important managerial implications that may be essential for developing CPS in SPL

Developing digital dashboards (DD) that support staff in monitoring, identifying anomalies, and facilitating corrective actions are decisive for achieving the benefits of Smart Production Logistics (SPL). However, existing literature about SPL has not sufficiently investigated the characteristics of DD allowing staff to enhance operational performance. This conceptual study identifies the characteristics of DD in SPL for enhancing operational performance of material handling. The study presents preliminary findings from an ongoing laboratory development, and identifies six characteristics of DD. These include monitoring, analysis, prediction, identification, recommendation, and control. The study discusses the implications of these characteristics when applied to energy consumption, makespan, on-time delivery, and status for material handling. The study proposes the prototype of a DD in a laboratory environment involving Autonomous Mobile Robots.

Developing cooperative serious games has specific challenges of enabling players to achieve both gaming and learning goals in a cooperative fashion. The complexity of handling game and learning requirements leads to the lack of guidance for systematically developing cooperative serious games (SGs). To overcome the challenges, we propose a systematic approach to utilize elements of entertainment cooperative games to foster player engagement in SGs. The guideline, which consists of steps to transform the existing cooperative entertainment games into cooperative SGs, is proposed. To demonstrate the guideline application, we developed a game prototype follow the steps. To validate our guidelines, we conducted a user study to verify games for their learning potential. Learning objectives related to urban logistics are defined and limited the scope of our research. We ask participants to do pretest and posttest to measure their memorization. The study showed that the game developed followed by our method could support players to achieve learning objectives.

The development of cooperative serious games has specific challenges related to enabling players to achieve both gaming and learning goals in a cooperative fashion. The complexity of gameplay and learning objectives leads to the lack of guidance for the systematic development of cooperative serious games (SGs). To overcome the challenges, we propose a systematic approach to utilize elements of entertainment cooperative games to foster player engagement in SGs called "Transforming Game Premise" to overcome the difficulties. A three-phase guideline is proposed for transforming an existing cooperative entertainment game into a cooperative SG. To demonstrate the application of the proposed guideline, we developed a game prototype that follows the guided steps. We validate the guidelines by conducting two user studies. The first study aims at validating the game's effectiveness for learning purposes of a game developed according to our guidelines. The study showed that the developed game supports players in achieving the defined learning objectives. The second study is a qualitative study evaluating game developers' perception of the usability and usefulness of the Transforming Game Premise guideline. The latter study confirms that the proposed guideline is beneficial for systematically developing SGs. However, it also indicates that the guideline still needs more clarity in identifying the relation between game elements and players' interaction/cooperation.

The study analyzes the application of reinforcement learning (RL) for material handling tasks in Smart Production Logistics (SPL). It presents two contributions based on empirical results of a RL model in dynamic production logistics environment from the automotive industry. Firstly, an architecture integrating the use of RL in SPL. Secondly, the study defines various elements of RL (environment, value, state, reward, and policy) relevant for training and validating models in SPL. The study provides novel insight essential for manufacturing managers and extends current understanding related to research combining artificial intelligence and SPL, granting manufacturing companies a unique competitive advantage.

Recent studies suggest that data-driven decision-making facilitated by Digital Twins (DTs) may be essential for optimizing resources and diversifying value creation in production logistics. However, there exists limited understanding about the design of DTs in production logistics. Addressing this issue, this study proposes a process for the design of DTs in production logistics. This study extends related works describing the dimensions of DTs in manufacturing, and adopts a process perspective based on production development literature. The results present a process for the design of DTs including activities in pre-study, conceptual, and detailed design phases corresponding to five DT dimensions. The proposed process is validated during the development of a DT in a production logistics lab at an academic environment. The findings of this study may be essential for avoiding misplaced resources and lost opportunities in the design of DTs in production logistics, and facilitating the planning and resource allocation.

Supply chain visibility (SCV) has been gaining recognition in recent years as a key factor for achieving analytical capabilities and improving supply chain performance. However, levels of SCV implementation lag behind current technological advances. This research was motivated by the lack of visibility in inbound logistics, which limits the possibility of managing deviation, in particular concerning changes in arrival time of incoming goods, in large industrial firms. We addressed this problem by adopting a design science approach. In particular, we followed context–intervention–mechanism–outcome (CIMO) logic to map and analyse material and information flows. The problems areas were successively translated via business and functional requirements into technological solutions. We evaluated alternative technologies using controlled experiments that mimicked real-life situations. This study provides guidance for manufacturing companies aiming to enhance deviation management and predictive capabilities by improving visibility in their inbound logistics and potentially extending visibility to other areas, such as internal and outbound flows.

Events such as Covid-19 have revealed the vulnerabilities that companies face due to low visibility. Consequently, companies experience impact on their supply chains in terms of disruptions of material supply, deliveries, productivity and revenue. Thus, the importance of Supply Chain Visibility (SCV) in global and competitive markets with increasing sustainability demands has received widespread recognition. Yet, the literature provides limited understanding of requirements to consider when developing a SCV system. Addressing the gap, this study presents the findings from a case study during the first months of 2021 at a global manufacturing company developing a SCV system to improve their inbound flow. Using a system engineering perspective, this study presents requirements highlighted during early stage for a SCV system. The results indicate the importance of ensuring SCV system requirements to enable data collection, handling and usage for decision making leading to both supply chain sustainability and resilience. This study contributes to the understanding of SCV by presenting and categorizing requirements considered for real-time case at a manufacturing company when developing a SCV system.

Supply chain visibility is a concept that is gaining increasing attention. Increasing levels of visibility in the supply chain is considered beneficial in many respects. A systematic literature review identified 47 empirical research papers from international scientific journals. Two main findings emerged from the content analysis. First, the perspectives provided in the extant literature can be grouped into four categories: antecedents, barriers and challenges, drivers, and effects. The effects include both capabilities and operational performance. Second, the few models on supply chain visibility include only antecedents and effects, and do not capture the perspectives of barriers, challenges, or drivers. We present a framework for supply chain visibility driven by insights from the content analysis. The ABCDE framework includes antecedents (A), barriers and challenges (BC), drivers (D), and effects (E), and provides a holistic view of supply chain visibility. The framework can aid managers with per-spectives and factors to consider when discussing, implementing, and improving supply chain visibility and provides researchers with a state-of-the-art review of supply chain visibility. We also propose an agenda for further research.

Globalisation, competitive markets and increasing sustainabilityrequirements are demanding companies to focus on visibility to improve theirsupply chains and ultimately their businesses. This paper aims to identifyperspectives, principles and prospects of production logistics visibility (PLV). Thestudy is based on a literature review of articles presenting definitions, developmenttrends and the future role of PLV. It is concluded that visibility is generally definedby availability, quality, accessibility and usefulness of information. PLV could referto the extent to which actors within the production systems have access to timelyand accurate information considered useful to their operations. According to thefindings, antecedents of PLV include digitalisation, IoT and connectivity. Thesesteps are required to turn data into meaningful information that can be used fordecision making in production and logistics setting to improve operational andbusiness performance. Furthermore, to fully benefit from PLV, there has to be anintegration of external and internal perspectives. Concluding, the paper definesfuture research efforts including four lines of exploration and development: (1)Intra-site visibility for material management including dynamic synchronisation,takt and resource planning. (2) Supply-oriented visibility for dynamic status andprediction of supply network status. These two initial lines of enquiry should includethe perspectives of stakeholders, parameter, enabling technologies and potentialimpact. (3) A synthesised framework for Production Logistics Visibility, relying onutilizing antecedents and enabling multi-criteria decision in production logisticsbased on visibility, where performance in terms of efficiency, sustainability andflexibility is ensured. (4) To specifically detail and exploit the potential inproduction logistics visibility in the aspect of environmental sustainability andclosed material and product loops 

Supply Chain & logistics as a subject lends itself readily to game-based learning. SCM subject learning is primarily about decision making, logistics and strategic management of resources. Most of the serious games designed for SCM are used in a workshop setting, and much of the learning outcome is achieved through the debriefing part of the workshop, i.e., not as an integrated part of the game. However, many such serious games expose their internal mechanics too easily. This side effect coupled with high development costs and limited and often constrained assessment schemas are reasons for low uptake. Another aspect is that games age and thus can often not be used for a long period. The usage of commercial off the shelf games might be a solution, but it requires that the game can be modded to fit the intended learning outcomes in the course it should be used. This article reports on the work carried out to identify if such a game, not specifically designed for the specific curriculum of SCM, can be used or not.

Digital Twins are increasingly perceived as critical enablers forimproving operational performance and sustainability of Smart ProductionLogistics. Addressing the lack of empirical research on this topic, this studyexplores the economic, environmental, and social sustainability impact ofDigital Twin-based services for Smart Production Logistics. The study presentsfindings from a Smart Production Logistics demonstrator in an academicenvironment and underscores the contributions and limitations of currentunderstanding about Digital Twin-based services in relation to their impact oneconomic, environmental, and social sustainability. The study presents valuableimplications for managers responsible for material handling.

The rapid uptake of electric vehicles (EVs) will be vital to decarbonise the transport sector and achieve climate change targets. However, this transition is leading to an increased demand for key battery materials and associated resource challenges and supply-chain risks. On the other hand, discarded EV batteries create business opportunities for second life and recycling. This study presents scenario-driven material flow analysis (MFA) to estimate the future volume of EV battery wastes to be potentially generated in Sweden and future demand for key battery materials, considering potential EV fleet, battery chemistry developments, and end-of-life strategies of EV batteries. Further, we combine MFA with a socio-technical approach to explore how different socio-technical developments will affect both EV battery flows and the underlying systems in the future. Recycling has the potential to reduce primary demand by 25–64% during 2040–2050 based on projected demand, meaning that waste streams could cover a considerable part of the future raw material demands. Second-use of EV batteries can promote circularity yet postpones recycling potentials. From a transition perspective, promoting recycling, second-life use of EV batteries and advanced battery technologies entail system disruption and transformational changes in technology, markets, business models, policy, and infrastructure and user practices. Demand for high-capacity batteries for grid decarbonisation and aviation applications may contribute to the emergence of niche battery technologies. Each scenario highlights the need for effective policy frameworks to foster a circular EV battery value chain.

How to design Human–Industrial Robot Collaborative (HIRC) workstations is one of the key challenges in the realisation of safe and efficient HIRC systems in industry. The aim of this paper is to present a simple method to be used in early phases of HIRC workstation design. The design method requires a simulation tool and is based on systematic design methodologies and its reference work, Pahl and Beitz´s engineering design framework. The proposed HIRC design method consists of four phases: planning and clarifying the work task, conceptual design, embodiment design and detail design, where iteration loops back to previous phases are vital. This design method is applied in an industrial HIRC design case on assembly of a flywheel cover on a heavy vehicle engine block. In this application example, a previously developed HIRC simulation software is used to generate quantitative values on identified evaluation criteria, in this case operation time and biomechanical load. This proposed HIRC design method in combination with any type of simulation tool enables the systematic design of HIRC workstations early in the production development process. 

Facility layout design is becoming more challenging as manufacturing moves from traditionally emphasised mass production to mass customisation. The increasing demand for customised products and services is driving the need to increase flexibility and adaptability of both production processes and their material handling systems. A holistic approach for designing facility layouts with optimised flows considering production and logistics systems constraints seems to be missing in the literature. Several tools, including traditional methods, analytic hierarchy process, multiple-attribute decision making, simulation, and optimisation methods, can support such a process. Among these, simulation-based optimization is the most promising. This paper aims to develop a facility layout design methodology supported by simulation-based optimisation while considering both production and logistics constraints. A literature review of facility layout design with simulation and optimisation and the theoretical and empirical challenges are presented. The integration of simulationbased optimisation in the proposed methodology serves to overcome the identified challenges, providing managers and stakeholders with a decision support system that handles the complex task of facility layout design.

Simulation-based participatory modelling allows integration of all types of knowledge including empirical, technical and scientific from all disciplines and domains. Thus, in recent years, the use of participatory modelling has been continuously increasing in many fields including logistics. With a view of achieving better understanding of the subject, this article systematically reviews the advances made in participatory modelling in the field of urban and production logistics in the last decade. It further reports the findings transparently following a categorization based on (i) the purpose of participatory modelling in the domain, and (ii) depending on the purpose how data is collected, processed and outcomes are presented. The review resulted in 97 articles which were analysed and categorized based on the above two questions formulated in the literature surveyed. The review revealed that apart from the three existing categories of purposes, namely, reflexive, descriptive and normative there is an emerging fourth category that was analytical in nature and 15 out of 97 articles analyzed belonged to this category. The authors decided to call this category analytical field empirical modelling which is primarily based on mathematical modelling and use of computational methods. We present these results with the help of a categorization. During the analysis for the second research question, we discovered that though the conventional ways of data collection and processing, such as interviews and workshops, which remain significantly present, in electronic data crowdsourcing and data processing via computational methods are emerging. 

Cities are growing and sustainable urban mobility planning (SUMP) is gaining in importance with it. The problems in the domain often involve multiple stakeholders with conflicting or competing objectives. The stakeholders and objectives can be local to certain neighborhoods or apply to the global city-wide scale. We present a methodology to address such problems with the help of modern simulators and multi-objective evolutionary algorithms. The methodology brings all stakeholders to the table and presents to them a near optimal set of alternatives to choose from. As an example, we consider the problem of minimizing vehicular noise in a particular neighborhood while also minimizing city-wide emission for heavy vehicles. We describe the requirements and capabilities of the simulator and the optimization algorithm in detail and present a methodology to model both local (noise reduction) and global (emissions) objectives simultaneously. We apply our methodology on two large city scale case studies and present our findings.