While Industry 4.0 has been trending in practice and research, operations management studies in this area remain nascent. Our intent is to understand the current state of research in Industry 4.0 in ...different disciplines and deduce insights and opportunities for future research in operations management. In this paper, we provide a focused analysis to examine the state-of-the-art research in Industry 4.0. To learn about researchers' perspectives about Industry 4.0, we conducted a large-scale, cross-disciplinary and global survey on Industry 4.0 topics among researchers in industrial engineering, operations management, operations research, control and data science at the 9th IFAC MIM 2019 Conference in Berlin in August 2019. By using our survey findings and literature analysis, we build structural and conceptual frameworks to understand the current state of knowledge and to propose future research opportunities for operations management scholars.
Glossary of Abbreviations
AGV: Automated guided vehicle; AI: Artificial intelligence; APS: Advanced planning system: a wide variety of software tools and techniques, with many applications in manufacturing and logistics (including the service sector); BDA: Big data analytics; CAS: Complex adaptive system: a system composed of many interacting parts that evolve and adapt over time; CIM: Computer integrated manufacturing; CPFR: Collaborative planning, forecasting and replenishment; CPS: Cyber-physical system: a seamless integration of computation and physical components; DAMCLS: Decision analysis, modelling, control and learning systems; ERP: Enterprise resource planning; FMS: Flexible manufacturing system; I4.0: Industry 4.0; IFAC: International Federation of Automatic Control: a federation is concerned with the impact of control technology on society; IME: Industrial and mechanical engineering; IoT: Internet-of-Things; IT: Information technology; M2M: Machine-to-machine; MAS: Multi-agent system: a loosely coupled network of software agents that interact to solve problems that are beyond the individual capacities or knowledge of each problem solver; OR: Operations research; RFID: Radio frequency identification: a technology that uses electromagnetic fields to automatically identify and track tags attached to objects; RMS: Reconfigurable manufacturing system: a manufacturing system that can change and evolve rapidly in order to adjust its productivity capacity and functionality; OM: Operations management; T&T: Track and trace system; VCA: VOS viewer co-occurrence analysis: a software tool for visualising bibliometric networks; VMI: Vendor-managed inventory.
This paper describes an innovative and integrated approach to component management optimization within a production/assembly system. In a mixed-models assembly process the handling of parts and ...components for each work station represents a substantial variable that can greatly affect job duration and efficiency. This paper is strictly related to Assembly to Order/Manufacturing to Order (ATO and MTO) systems, where lead time has to be very short and flexibility is at its maximum level. In Assembly to Order (ATO) or Make to Order (MTO) systems, the production is increasingly getting more customized in response to the demand, thanks to the progresses reached in both manufacturing and information technologies. It is becoming increasingly possible to assemble or make products specifically in response to the requests of either end customers or retailers. As a consequence of such customization, the design of the whole system must take into direct account several elements: parts warehouses location, feeding policies and feeding systems. In some cases the collection of parts and components required picking activities, in other the movement of entire units load.
In several instances experts have analyzed the problems about material centralization/decentralization, storage policies and assembly feeding problem in different and independent ways, while the problem needs an integrated approach. While many researches regarding components allocation problems in ATO and MTO systems, did not consider feeding policies, material picking, packing activities and vehicles optimization, this paper cover focuses on filling such gap using an integrated framework that considers both aspects of the problem: the centralization/decentralization of components in order to minimize the total storage costs and the right feeding policies.
Feeding problems in assembly lines are some of the most important aspects to consider during the analysis and design of an assembly system, to allow the maximization of efficiency and flexibility. To reach such goals, a multi-factorial analysis has been carried out during this experiment and will validate the introduced framework. An industrial application of the introduced framework is illustrated to explain its real significant production implication.
Sustainability in parcel delivery is a growing area of interest, especially for third-party logistics providers (3PLs). The recent increase of urban population is directly related to the increase ...request of goods in urban areas, and consequently to the growth of the urban freight transport and CO2 emissions. For these reasons, national and local institutions carried out regulations and incentives to reduce urban pollution and promote zero-emission vehicles. In particular, daily tickets to access to city centers is a common regulation applied to reduce freight transport. This paper presents a new SPD model that compares Eclectic Vehicles (EVs) and Fossil Fuel Vehicles (FFVs) considering economic savings and CO2 emissions, for parcel delivery from a single distribution center to a set of delivery point located inside and/or outside an urban area. Limitations as the daily ticket, the fuel cost, the battery duration are considered to provide 3PLs an innovative model to evaluate both the economic convenience and the environmental impact of its vehicles fleet. Through an explanatory study, economic considerations are carried out, related to the length of the route, the daily ticket cost, and the fuel cost to evaluate and to assess the different transportation options. It demonstrates that EVs are more convenient in terms of economic savings when the route (urban distances) and the daily ticket cost increase.
In order to control the time to market and manufacturing costs, companies produce and purchase many parts and components before receiving customer orders. Consequently, demand forecasting is a ...critical decision process. Using modular product design and super bills of materials are two effective strategies for developing a reliable demand forecasting process. They reduce the probability of stockouts in diversified production contexts. Furthermore, managing and controlling safety stocks for pre-assembled modules provide an effective solution to the problem of minimizing the effects of forecast errors. This paper develops, evaluates, and applies innovative cost-based analytical models so that the optimal safety stock of modular subassemblies and components in assembly to order and manufacturing to order systems, respectively, can be rapidly quantified. The implementation of the proposed models in two industrial case applications demonstrates that they significantly reduce the safety stock inventory levels and the global logistical cost.
Supply chain network design (SCND) is a key strategic decision in supply chain management (SCM). One particular area of SCND is concerned with disruption risk modelling. This paper presents a ...systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics. More specifically, our analysis is focused on different costs induced by the planning of proactive investments in robustness and through parametrical/structural adaptation at the recovery stage. This review can be of value for researchers and decision-makers alike for several reasons. First, we categorise the existing knowledge based on decision-making problems, which can be instructive for a convenient association of a particular SCND problem to a modelling domain according to network-wise, supply-side and demand-side perspectives. Second, our analysis focuses on the costs specifically induced by disruption risks and resilience investments. Third, we offer a dedicated section related to disruption probability formulation methods and their impact on resilience costs. Fourth, the integration of different SCM dimensions (i.e., social impact, environmental impact, responsiveness, and risk-aversion) and the associated multi-objective modelling settings are discussed along with disruption risks in SCND models. Finally, we summarize our findings as insights from a managerial perspective. Drawbacks and missing aspects in the related literature are highlighted, and we lay out several research directions and open questions for future research.
•Development of supply chain resilience portfolio approach.•Mathematical model for optimizing resilience portfolio efficiency.•Working tool for decisions on investments in resilient redundancy ...allocation.•Decision-support for efficient recovery deployment.
Supply chain (SC) resilience is imperative to cope with disruptions using some preparedness and recovery capabilities such as network redundancy (e.g., backup suppliers) and process flexibility (e.g., capacity agility). These capabilities frame an SC resilience portfolio. Both designing a resilient portfolio and recovering in case of a real disruption require investments. This paper presents a new mathematical model for designing an efficient resilience portfolio in a multi-echelon SC. Through computational and comparative analyses using a real-life case-study, we demonstrate that our model allows increasing resilience at minimal costs by determining an optimal combination of preparedness and recovery investments. Interestingly, the optimal solutions (i.e., efficient resilient SC designs) increase SC efficiency even in business-as-usual scenarios. This result contributes to the literature on transforming resilience from an expensive spend to a value-creation asset. We illustrate our approach using a real-life industrial example that allows for the identification of important relations between disruption duration/magnitude and efficiency of preparedness and recovery strategies. Based on computational, comparative, and case-study analyses, we deduce and generalize managerial implications at the network, supplier, and manufacturer levels. We take an extra step by extrapolating our major findings and generalized managerial implications toward the COVID-19 pandemic setting. The outcome of our research can be instructive for SC managers when deciding on investments in resilient redundancy allocation as a part of preparedness strategy and efficient recovery deployment.
Background Worldwide, the worker population age is growing at an increasing rate. Consequently, government institutions and companies are being tasked to find new ways to address age-related ...workforce management challenges and opportunities. The development of age-friendly working environments to enhance ageing workforce inclusion and diversity has become a current management and national policy imperative. Since an ageing workforce population is a spreading worldwide trend, an identification and analysis of worker age related best practices across different countries would help the development of novel palliative paradigms and initiatives. Methods This study proposes a new systematic research-based roadmap that aims to support executives and administrators in implementing an age-inclusive workforce management program. The roadmap integrates and builds on published literature, best practices, and international policies and initiatives that were identified, collected, and analysed by the authors. The roadmap provides a critical comparison of age-inclusive management practices and policies at three different levels of intervention: international, country, and company. Data collection and analysis was conducted simultaneously across eight countries: Canada, France, Germany, Italy, Japan, New Zealand, Slovenia, and the USA. Results and conclusions The findings of this research guide the development of a framework and roadmap to help manage the challenges and opportunities of an ageing workforce in moving towards a more sustainable, inclusive, and resilient labour force.
The workforce ageing phenomenon is recently affecting most of the Organisation for Economic Co-operation and Development (OECD) member countries, due to a general ageing of their populations and a ...higher average retirement age of the workforce. In this paper, the topic of ageing workforce management is addressed from a production research standpoint, with the aim of understanding how older workers can be supported and involved in a manufacturing system. First, the current state of the art related to the ageing workforce in production systems is presented. This is structured according to four main topics: (1) analysis and evaluation of ageing workers' functional capacities, (2) consideration of ageing workers' capacities in industrial system modelling and management, (3) analysis and exploitation of ageing workers' expertise, (4) acknowledgement, analysis, design and integration of supporting technologies. Next, the discussion on the impact of the ageing workforce on manufacturing systems' performances leads to the comparison of some technological advances that are related to the Industry 4.0 paradigms. Finally, a future research agenda on this topic is proposed, based on the same topics classification proposed for the literature analysis. Five different research areas are derived, suggesting future directions for appropriate research concerning the employ of older workers in production environments.
Traditional inventory models involve different decisions that attempt to optimize material lot sizes by minimizing total annual supply chain costs. However, the increasing concern on environmental ...issues stresses the need to treat inventory management decisions as a whole, by integrating economic and environmental objectives. Recent studies have underlined the need to incorporate additional criteria in traditional inventory models in order to design “responsible inventory systems”. This paper explores the integration of factors affecting the environmental impact within the traditional EOQ model and proposes a “Sustainable EOQ Model”. All sustainability factors linked to the material lot size are analyzed from the beginning of the purchasing order to the end of its life inside the buyer plant. Thus, the environmental impact of transportation and inventory is incorporated in the model and investigated by an economic point of view. In particular internal and external transportation costs, vendor and supplier location and the different freight vehicle utilization ratio are considered in order to provide an easy-to-use methodology. The optimization approach is applied to representative data from industrial problems to assess the impact of sustainability considerations on purchasing decisions if compared with the traditional approaches. Finally, an illustration of the effect of using the new “Sustainable EOQ model” is presented and discussed.
The new Industry 5.0 paradigm complements the well-known Industry 4.0 approach by specifically driving research and innovation to facilitate the transition to sustainable, human-centric and resilient ...industry. In the manufacturing context, workers' diversity in terms of experience, productivity and physical capacity represents a significant challenge for companies, especially those characterized by high staff turnover and manual processes with high workload and poor ergonomics. In seeking to address such challenges, this research adopts a human-centric perspective to define new flexible job arrangements by developing a new multi-objective job rotation scheduling model. The proposed model is unique in that it aims to achieve multiple job assignment objectives by simultaneously considering different socio-technical factors: workers' experience, physical capacity and limitations, postural ergonomic risks, noise and vibration exposure, and workers' boredom. The model's implementation in real environments can be supported by new sensor-based technologies that collect data on workers' efficiency, ergonomic scores and task performance and enable workers to participate in measuring perceived fatigue and boredom. The primary goal of our model is to find the most appropriate assignment of job and individual-flexible rest-break plan for each worker. The authors test the model application in an industrial setting. Useful managerial insights emerge and prescriptive recommendations are provided.
•Flexible job scheduling and workforce organization in manufacturing and logistics systems according to I5.0 paradigms.•Job rotation scheduling model capable of integrating 3 different work aspects: productivity, ergonomics and workers' boredom.•We evaluate the impact of human factors and ergonomic criteria on system performance and workers' safety.•Managerial insights for the workforce job assignment considering individual worker characteristics and limitations.
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