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A Literature Review on the Cross-Domain Usage of Digital Factory Twins Within Design Time
No full textPart 3: Hybrid Intelligence – Decision-Making for AI-Enabled Industry 5.0International audienceIn a globalized production environment companies are confronted with shortening product life cycles leading to shortening factory system life cycles. To overcome this issue, factories have to be (re-)built faster. The design time is a crucial phase in which many different disciplines of different domains have to work together in a major planning project. Currently, various experts in the respective domains of e.g. production system planning, automation and building are commonly working on their silo models resulting in different and sometimes contradictory information depending on the perspective of planning. While model-orientated, collaborative planning approaches like Building Information Modeling (BIM) have become familiar with the domain of factory planning, there is still a lack of combining the different factory data models holistically to connect all elements of production regarding information of products, processes and resources. Besides the BIM methodology several other forms of virtual factory descriptions, like the digital factory twin have emerged. In this work, a systematic literature review is conducted to present the current perspective on creating factory data models about a cross-domain usage and modeling approach. In analyzing the current use case definition of factory models the opportunity is seen to point out the importance of the combination of holistically linked factory data models with a multipurpose design. In doing so, a possibility is seen to overcome the mentioned obstacles of planning while raising the value of the created models. This demonstrates the need for a concept of modeling a digital factory twin, created for cross-domain usage
Research Interpretation of Article 14 of the EU AI Act: Human in Command in Manufacturing
No full textPart 2: Human in Command – Operator 4.0/5.0 in the Age of AI and Robotic SystemsInternational audienceThe rapid integration of artificial intelligence (AI) into various sectors necessitates rigorous frameworks to ensure that human oversight remains central, aligning with regulatory requirements such as Article 14 of the European Union’s AI Act. This paper introduces the “Human in Command” model, a novel approach designed to foster effective human-AI collaboration, particularly in manufacturing environments. Our model is bifurcated into two primary components: Design4Command and FeelingInCommand. Design4Command outlines a comprehensive set of methodologies for constructing human-AI-teams that emphasize human leadership and decision-making authority, ensuring that AI systems enhance rather than replace human capabilities. FeelingInCommand, on the other hand, presents innovative metrics and tools for assessing the psychological and ergonomic factors impacting humans’ perception of control and efficacy when interacting with AI systems. Using this model, organizations can optimize the efficiency and satisfaction of human operators in AI-enhanced settings. This paper details the theoretical underpinnings of our approach, the design principles of our methodologies, and potential applications across various domains, offering a guideline for developers and policymakers aiming to preserve human oversight in the age of AI
The Facets of ‘Respect for People’ Principle: A Systematic Review and Thematic Analysis of the Literature
No full textPart 1: Lean Thinking Models for Operational Excellence and Sustainability in the Industry 4.0 EraInternational audienceThe core of lean is formed by two key principles: continuous improvement (CI) and respect for people (RFP). Although lean holds a lot of promise to improve operations, the implementation success rate outside of Japan is still fairly low. Recent literature shows that one of the main reasons for failed implementation is a lack and poor understanding of RFP principle, which results in reduced people involvement. This paper aims to improve the understanding by exploring the prevailing discourses in lean literature related to the RFP principle to distil dominant themes which break this complex concept into facets that could be systematically studied. For this purpose, we propose a systematic literature review of 26 articles published in 21 peer-reviewed international journals that explicitly discuss RFP principle. Four themes emerged from the analysis, and three RFP facets were distilled from these themes. The analysis shows that all of RFP facets must be in place to enhance people's involvement in problem-solving. A specific relation between the facets is observed that needs to be acknowledged when RFP is considered. The results also show that RFP enables CI and complements it as an intervention in its own right. While this study is far from exhaustive, we believe the results will introduce additional clarity and improve the utility of the complex RFP principle for research and practice
Exploring Agile Methods Application in Manufacturing
No full textInternational audienceIn the contemporary business environment, production and manufacturing organizations face increased customer demands, market volatility, and various constraints. These challenges require the implementation of new methods to stay competitive, especially the utilization of digital technologies. Recently, agile principles and methods have spread into the manufacturing business. Therefore, this paper explores the applications of agile methods in manufacturing organizations and how they enhance production in terms of speed, cost-effectiveness, and quality. A mixed research methodology relying on a systematic literature review and interviews is adopted. The analyzed papers present the increasing developments in agile manufacturing since 2019. We found that agility is addressed as a capability for manufacturing to operate a business in an uncertain environment and react flexibly to serve customer demand. The results uncover significant opportunities and challenges for agility enhancement, which could be useful for production and operations managers
Optimization of Reconfigurable Manufacturing Systems Configuration Using Constraint Programming
No full textPart 1: Smart Manufacturing Assets as Drivers for the Twin Transition Towards Green and Digital BusinessInternational audienceTo cope with market unpredictability and uncertainty, manufacturing industries should be able to rapidly adapt their manufacturing systems to be more responsive to market changes. Reconfigurable Manufacturing Systems (RMS) offer an alternative to traditional manufacturing systems. They can rapidly reconfigure and readapt their capability and functionality to meet new requirements without the need to start from scratch. RMS are complex systems and a critical phase in their implementation involves their design. We propose a new constraint programming approach to minimize the total investment cost of a multi-part flow line configuration. The approach was implemented and tested on a literature case study. The results show the ability of the method to find an optimal solution in few seconds for a small instance
Navigating Lifecycle Management Models: Testing of a Lifecycle Management Framework for Product-Service Systems
No full textPart 4: Methods and Tools to Achieve the Digital and Sustainable Servitization of Manufacturing CompaniesInternational audienceThere is a gap between the concepts of Product-Service System (PSS) and Lifecycle Management (LCM) models. This study highlights the organisational hurdles in assimilating PSS into existing LCM frameworks, emphasising the disconnect between current models and the dynamic digital transformations reshaping organisational landscapes. It argues that the inability of existing LCM frameworks to accommodate the rapid pace of digitalisation is a critical barrier to effective PSS management, underscoring the need for a digital-inclusive approach to LCM. This paper takes a case study approach, examining various industry cases and describing organisations’ practical struggles aligning PSS LCM frameworks with digital advancements and organisational dynamics. These real-world examples provide a foundation for developing a novel, comprehensive PSS LCM framework that integrates digital tools and systems as central components. This proposed framework aims to enhance organisational adaptability, streamline processes, and foster better communication and collaboration within entities managing PSS. This study contributes to academic research and practical applications in PSS LCM, advocating for a more digitally integrated, organization-centric approach and offering a dual contribution of theoretical insights and practical implementations
The Generalized One-to-One Pickup and Delivery Vehicle Routing Problem
No full textPart 4: OptimizationInternational audienceVehicle Routing Problem (VRP), one of the most important problems in the logistics industry, aims to find the most suitable route for vehicles that meet the demands of customers. VRP is examined under various variants, and one of these variants, the Pickup and Delivery Problem, deals with the pickup demands as well as the delivery demands of the customers. This problem is divided into three main categories according to demand type and route structure: one-to-many-to-one problems, many-to-many problems, and one-to-one problems. In one-to-many-to-one problems, there are goods at the depot to be delivered to customers as well as goods at customers to be carried back to the depot. In many-to-many problems, one node can be the origin or destination point for a good, and multiple nodes can be the origin or destination point for each good, while in one-to-one problems, there is a single origin and a single destination point for each unique demand. Within the scope of this study, a general case of one-to-one problems is introduced, in which multiple vehicles are allowed to leave the depot with goods and return to the depot with undeliverable goods, and a customer can be both a pickup and delivery node at the same time. A mathematical model is developed for the problem to obtain the optimal solution for the test instances. The model is tested on 45 randomly generated test instances. The results show that 40 out of 45 instances were solved using a commercial solver within one-hour computation time limit
Material Shortages Propagation: Using Network Science to Evaluate Inventory Efficacy
No full textPart 2: Resilience Management in Supply ChainsInternational audienceThe ability to manage the effects of supply chain (SC) disruptions has played a major role in industrial environments in recent years. Pandemics, natural disasters, and political tensions increased difficulties in procuring components, resulting in delays in delivering finished products and thus in lost sales, along with other relevant effects that strained companies’ survivability (e.g. delayed financial flows). Companies have tried to avoid material shortages by increasing inventory levels, with increased costs and further risks (e.g., inventory devaluation, obsolescence), but with hard-to-evaluate benefits. Efficient resilience requires these cost-benefit analyses: their computation is even harder in today’s complex and intertwined supply networks (SN), where it is also hard to align SC players with contrasting goals. In this paper, we aim to understand the effect of increasing inventory levels in two different network types. Hence, we simulate the shortages of materials propagating through the SN. For the first time in this area of study, we extend the common SIR (susceptible, infectious, recovered) model to a SEIR (susceptible, exposed, infectious, recovered) model, where the state ‘E’ helps in modelling the time-dependent effect of different inventory levels to preserve operations. This paper’s practical value lies in offering a way for professionals to estimate the benefit coming from the investment in higher inventory levels, towards a choice that balances resilience and efficiency. On the theoretical side, we show that increasing inventory levels is more effective in SNs corresponding to scale-free network type (closer to automotive industry), compared to SNs corresponding to small-world type (typical of electronics industry)
Understanding Part Complexity: A Novel Approach for the Identification of Complexity-Influencing Part Characteristics
No full textPart 6: Advances in Production Management SystemsInternational audienceMachine tool manufacturers must understand the requirements of their customers to survive in challenging markets, e.g. by understanding their customers’ order characteristics. We want to explore part complexity as a measure to fill this gap of data-based customer information. This paper presents the procedure that we developed for part complexity assessment and is centered around expert consultation and the results from implementing this procedure at our industry partner, a machine tool manufacturer for sheet metal processing. Our contributions are (1) a literature review on part complexity and assessment approaches, (2) a definition of part complexity, (3) a tried-and-tested procedure for the assessment of part complexity including an online tool, (4) 80 sheet metal processing geometries, (5) codebooks containing the relevant part characteristics to assess part complexity of an exemplary production unit, (6) detailed explanation of the labeling results for three geometries, and (7) refinements for enabling transferring the labeling results to new geometries using a classification algorithm
Understanding Coopetition Dynamics in Manufacturing Value Networks: A System Dynamics Based Causal Loop Diagram (CLD) Modelling Approach
No full textPart 1: Modelling Supply Chain and Production SystemsInternational audienceThe concept of “coopetition” in manufacturing value networks involves firms engaging in both collaboration and competition simultaneously This approach, while aiming to leverage the benefits of both, inherently introduces a paradox concerning value creation and capture. Within a value network, coopetition involves various entities such as suppliers, distributors, subcontractors, and even competitors working together to enhance overall value. Despite a surge in research on coopetition, there remains a disjointed understanding, with limited exploration of its dynamics within manufacturing contexts. To address this gap, our study constructs a system dynamics model using causal loop diagrams (CLD) derived from an in-depth literature review within the manufacturing sector. Our aim is to comprehensively elucidate the factors influencing co-opetitive relationships and dynamics in manufacturing value networks and business ecosystems. Furthermore, existing literature emphasizes the need for a multifaceted perspective on coopetition in manufacturing. Our model, developed through consultation of extensive manufacturing and business literature and CLD application, identifies key factors driving coopetition dynamics in manufacturing and business ecosystem contexts. It represents the first comprehensive content analysis of coopetition dynamics within manufacturing and business ecosystems, serving as a valuable resource for scholars and professionals in the manufacturing and management field. By examining interconnected elements in a causal loop framework specific to manufacturing and business ecosystems, our study reveals how dynamic factors influence co-opetitive outcomes in these ecosystems. We explore various manufacturing-related aspects, such as supply chain dynamics in coopetition, technological innovations, and market dynamics, all impacting co-opetitive interactions. This comprehensive approach fills a literature gap, offering insights into critical factors affecting the co-opetitive process within manufacturing and business value networks. Our study’s methodology, employing causal loop diagrams tailored to the manufacturing domain, stands out in the literature, providing a unique perspective on coopetition dynamics within manufacturing and management contexts