Search

Due to the ever-changing dynamics of today's global market place, it is necessary to examine upcoming future trends that may impact businesses. Supply chains are a valuable component of all business planning, and hence, they must be continuously monitored. This paper reflects on the views and contributions of various authors writing on the crucial issue of managing supply chains. Specifically, topics such as relationship quality, performance, integration, responsiveness, risk management strategies, agility, and incentive systems in supply chains are addressed. [ABSTRACT FROM AUTHOR]

Manufacturing is undergoing a paradigmatic shift as it assimilates and is transformed by machine learning and other cognitive technologies. A new paradigm usually necessitates a new framework to comprehend it fully, organise extant knowledge, identify gaps in knowledge, guide future research and practice, and synthesise new knowledge. Paradoxically, such a framework to guide the research and practice of ML in manufacturing remains absent. This paper attempts to fill this gap by presenting the interpretive model of manufacturing as an integrative framework for ML in manufacturing. A systematic hybrid literature review approach has been adopted to conduct both thematic and conceptual synthesis of the literature. The descriptive literature review method has been used to conduct a thematic synthesis of the literature. The framework synthesis method has been used to complete a conceptual synthesis of the literature. The resultant framework, the interpretive model of manufacturing, is articulated as consisting of scan, store, interpret, execute, and learn as its purposive components. Research questions have been identified for each of these components, as well as at their interfaces, to develop a comprehensive and systematic research agenda. Additional areas for extending research have also been identified. Implications for manufacturing operations, manufacturing strategy, and manufacturing policy have been drawn out for practitioners and policy makers. [ABSTRACT FROM AUTHOR]

Artificial lighting is a constant companion in everyday private and working life, influencing visibility in interior spaces as well as outdoors. In recent years, new technical solutions have extended traditional lighting systems to become 'smart'. Different types of smart lighting systems are available on the market today, and researchers have concentrated on analysing their usability and efficiency, especially for private households, office buildings and public streets. This paper presents a systematic literature review to analyse the state-of-knowledge of technologies and applications for smart lighting systems. The results of the review show that smart lighting systems have been frequently discussed in the literature, but that their potentials in industrial environments, such as production and logistics, has rarely been addressed in the literature so far. Lighting systems for industrial environments often have very different requirements depending on the working environment and operating conditions. Based on the results of the literature review, this paper contributes to closing this research gap by discussing the usage potential of smart lighting systems to improve the efficiency of warehouse order picking, which is an application that may benefit from various functions smart lighting systems provide. Several propositions are developed that emphasise research opportunities and managerial implications in this context. [ABSTRACT FROM AUTHOR]

For manual picking processes in warehouses and assembly line feeding, collaborative robots – cobots – hold a potential to support operators and, thereby, enhance performance. However, studies focused on the economic aspects of cobot applications have been scarce. The present paper aims at modelling a new picking system, in which human operators collaborate with cobots during picking (or kitting) activities. It is considered the case of having a cobot on board of the picking trolley or cart, working in parallel with the picker by performing sorting of the picked items. The paper focuses on the economic aspects of this application and presents a model of the relative cost difference between a manual and a cobot-supported process, accounting for the costs associated with operators, equipment, and quality. The relative cost difference is analysed in a numerical example. The findings suggest that the decision to use a cobot sorting mode is robust when there is considerable sorting work to carry out, for example, when there are higher yearly order volumes to handle, and when higher order commonality among orders processed as a batch can be achieved. Future research should focus on implementation challenges and safety issues associated with cobot-supported picking processes. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the state-of-the-art analysis of some subarea of healthcare, surgery planning and scheduling, hospital operation management and regional healthcare delivery.

In this paper we present some of the recent advances in the quality and reliability engineering methodologies. These advances include change point detection, monitoring processes with correlated observations, monitoring and control of multivariate processes, integration of the statistical process control with engineering process control, accelerated life testing, degradation models, predictive maintenance, and software reliability engineering. Future directions of research in quality and reliability engineering and their challenges are also discussed. [ABSTRACT FROM AUTHOR]

The economic and social importance of the automotive industry explains the need for researching improved ways of organising and managing the diverse processes involved in the production of motor vehicles. Furthermore, the management of supply chains and inter-organisational relations has acquired strategic significance in recent years and has become a key area of research. At the interface between these two fields, this paper adopts a bibliometric viewpoint to analyse the scholarly literature that has addressed the study of supply chains within the specific sphere of the automotive industry. To do so, it has examined the 404 papers on this topic indexed through to 2011 in the Business Source Complete database. This has allowed identifying trends and opportunities related to the what, how and where of research into this matter. [ABSTRACT FROM PUBLISHER]

In robust parameter design, model parameter uncertainty and quality of experimental data often affect the establishment of response surface models, which in turn affect the acquisition of the optimal operating conditions. This paper proposes a robust multi-response surface modelling and optimisation method based on Bayesian quantile regression, which is a robust regression technique insensitive to outliers, to address the above problems. We first incorporate quantile regression into the Bayesian framework and use Bayes's theorem to obtain posterior inference of model parameters. Then, the Monte Carlo-based expectation maximisation algorithm is used to estimate the model parameters, and the entropy-based overall desirability function is taken asan optimisation objective to obtain the optimal settings. The effectiveness of the proposed method is demonstrated by an additive manufacturing process anda simulation study. Compared with other existing methods, the proposed method can resist the disturbance of outliers, and thus obtain more accurate optimisation results. [ABSTRACT FROM AUTHOR]

Extended warranties are widely adopted and accepted in the marketplace by manufacturers and retailers as it helps to enhance the customers' post-sale satisfaction. In closed-loop supply chains, the extended warranty not only generates profit for the manufacturer, but also provides warranty returns of the new products for remanufacturing. In this paper, a two-period model is developed and optimal pricing strategies for the extended warranties are derived. We compare the optimal pricing and retailing strategies of the extended warranties for remanufactured and new products offered by the manufacturer with and without the retailer's own extended warranty while considering the competition between the manufacturer and the retailer for the extended warranty of new products. We find that the introduction of the retailer's extended warranty does not always hurt the manufacturer's profit. Numerical analyses also show that there exists an optimal extended warranty length for the manufacturer that maximises its profit. Moreover, we show that the retailer cannot extract more profit by increasing the length of its own extended warranty. [ABSTRACT FROM AUTHOR]

Finite-State Automata (FSA) are foundations for modelling, synthesis, verification, and implementation of controllers for manufacturing systems. However, FSA are limited to represent emerging features in manufacturing, such as the ability to recognise and switch contexts. One option is to enrich FSA with parameters that carry details about the manufacturing, which may favour design and control. A parameter can be embedded either on transitions or states of an FSA, and each approach defines its own modelling framework, so that their comparison and integration are not straight-forward, and they may lead to different control solutions, modelled, processed and implemented distinctly. In this paper, we show how to combine advantages from parameters in manufacturing the modelling and control. We initially presenta background that allows to understand each parameterisation strategy. Then, we introduce a conversion method that translates a design-friendly model into a synthesis-efficient structure. Finally, we use the converted models is synthesis, highlighting their advantages. Examples are used throughout the paper to illustrate and compare our results and tooling support is also provided. [ABSTRACT FROM AUTHOR]

At the core of every high-performing warehouse is an efficient order picking (OP) system. To attain such a system, policy choices should be carefully aligned with subjects responsible for the actual picking within the established system. Despite recent advancements in automating the picking process due to Industry 4.0, human operators will continue to play a crucial role in the future of ware-housing. However, unlike robots, human operators have specific skills, conduct, and perceptions, which are only partly accounted for in current planning models. This review adopts a multimethod approach to identify and analyse how these phenomena are currently integrated into OP planning problems. In addition, we assess the relevance and adequacy of human factors modelling in academic literature with practice-based insights gathered via semi-structured interviews. This leads to five major human factors integration constructs and dedicated recommendations on how to refine them. We then take the analysis one step further and make suggestions on how to integrate these constructs with leading research methodologies in the context of Industry 5.0. The results highlight the prevalent need to increasingly account for psychosocial phenomena and their impact on operational performance. Future research opportunities provide a substantiated foundation to assist in human-centric work design. [ABSTRACT FROM AUTHOR]

With the great opportunities created by the new advances in Industry 4.0, many manufacturers are testing and investing in new equipment and infrastructure to deploy these technologies. However, there are a huge number of small and medium-sized manufacturers (SMMs) that are lagging behind due to the lack of in-house R&D capabilities and workforce shortage and/or financial constraints to afford such investment. Additionally, application of theoretical production research in SMMs often confront challenges such as low data availability and data quality, etc. In this paper, we describe a case study at a local medium-sized manufacturer of electromechanical devices for industrial, consumer, and medical applications, who was struggling to meet ever-growing market demand, and apply a novel approach of production system modelling to overcome the challenge of unavailability of the operation up-and downtime data. Specifically, the parametric model of the production system is identified using several system performance metrics derived based on the parts flow data of the in-process buffer. With the mathematical model constructed, the system bottleneck is analysed anda number of improvement scenarios are explored that can potentially enhance the system throughput. Finally, model sensitivity is analysed by calculating the deviation of the model-predicted performance metrics to those produced by a reference nominal model. This analysis demonstrates that the model constructed using our proposed approach is robust even when the system parameters vary from the baseline ones. [ABSTRACT FROM AUTHOR]

Due to today's competitive environment and information boom, companies are concerned about production planning in uncertain conditions. This paper integrates decision-making method with production scheduling model by considering limited resources. In this paper, a new mathematical model is extended for production project scheduling with multiple execution modes. The main aim of the formulation is to plan and schedule real production projects in uncertain environments. A new mixed-integer linear formulation is presented by considering trade-off of cost, time, as well as quality. Cost–time-quality trade-off is extended with the interval information. In the presented model, activity quality could be enhanced by reworking. The interval forms of some parameters, including duration, quality of activities, cost, and total available resources, are obtained by determining weights of experts and aggregating them. The presented group decision-making method is based on a bi-directional projection measure to deal with interval information. Since the mathematical model is multi-objective and some data are interval, a new modified solution method is developed for solving the model. The presented method for both decision-making and mathematical models is investigated by a real-world production project and two datasets to ascertain the accuracy of the model. Finally, an appropriate sensitivity analysis is proposed. [ABSTRACT FROM AUTHOR]

This paper studies a cooperating mode selection problem of a manufacturer who sells its products through an offline channel and an online platform under cap-and-trade regulation. The platform can operate with marketplace or reselling mode. We investigate the manufacturer’s optimal operational decisions and selection of the platform’s modes considering demand disruptions. First, when the carbon cap decreases in the application process, this regulation is firstly easy and then hard to be implemented if the cross-channel effect is small. Even though the platform increases its commission rate, greater cross-channel effect can still bring more production. Second, the increase of demand disruptions brings more profits for the manufacturer and the platform. Specifically, considering demand disruptions, the total profit with reselling mode in decentralised case is larger than that in centralised case under some situations. Third, without demand disruptions, the manufacturer prefers marketplace mode (reselling mode) if the commission rate is low (high). However, demand disruptions make the manufacturer’s mode selection a little complicated. Lastly, without demand disruptions, the two firms can be coordinated with reselling mode but cannot be coordinated with marketplace mode. With demand disruptions, the two firms can be coordinated with the two modes in some situations. [ABSTRACT FROM AUTHOR]

Coronavirus (COVID-19) is a highly infectious respiratory disease which spread can be effectively curbed by wearing facial masks, especially N95 and surgical masks. In this paper, we develop a stylised game-theoretical model to evaluate the impacts of producing and selling masks on supply chain profits, safety index and consumer and social welfare. Firstly, we find that as the infection probability without protection (IPWP) increases, both the retail price and demand for these masks will increase. When the IPWP is sufficiently low, those consumers who want to purchase masks are more likely to purchase N95 masks, but when the IPWP increases, surgical masks are more popular amongst consumers. Secondly, we develop a safety index that indicates the effectiveness of using masks in preventing respiratory disease infection. This index is especially crucial in cases where the IPWP is moderate; in other words, recommending to wear masks is particularly important when the IPWP is moderate. We also examine the impacts of government involvement in handling the outbreak of respiratory diseases. Providing consumer subsidies and promoting the social mask enterprise can effectively combat respiratory diseases under different conditions. Our results can be used for combating COVID-19 and preparing for future health crisess. [ABSTRACT FROM AUTHOR]

This paper presents a novel quantitative approach and stochastic quadratic optimisation model to maintain supply chain viability under the ripple effect. Instead of viability kernel commonly used in the viability theory, this paper establishes the boundaries on acceptable production states for which the production can be continued under the ripple effect, with no severe losses. For a given implementable portfolio of controls, the boundaries on acceptable production trajectories associated with the two conflicting objectives, cost and customer service level are determined. The decision maker selects a viable production trajectory in-between the two boundary trajectories: the cost-optimal and the service-optimal. The selection depends on the decision maker preference, represented by a chosen weight factor in the optimised quadratic objective function that minimises weighted deviations from the cost-optimal and from the service-optimal production schedules under the ripple effect. The findings indicate that for the extreme values of the weight factor, the viable production trajectory is inclined toward the corresponding boundary trajectory and remains in-between the two boundaries, when both objectives are equally important. Keeping production trajectory in-between the two boundaries makes the supply chain more resilient to disruption risks, while the supply chain resilience diminishes as the production trajectory approaches a boundary trajectory. Then a more severe disruption may push the production outside the viability region and cause greater losses. [ABSTRACT FROM AUTHOR]

Cross-docking is a logistics procedure implemented in a warehouse to achieve a competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. Today, one of the challenges related to cross-docking for both practitioners and researchers is handling the uncertainty. Robust cross-docking solutions bring a part of the answer to this challenge. This paper proposes an overview of robust and real-time models for cross-dock problems with a focus on scheduling problems, notably in the road-to-road cross-dock environment. To this end, the conducted systematic literature review addresses the collection, identification, screening, eligibility, and inclusion steps to extract the most relevant literature. The gaps in the literature are identified, and some perspectives to support future studies are proposed. [ABSTRACT FROM AUTHOR]

Job shop scheduling problem (JSP) is a widely studied NP-complete combinatorial optimisation problem. Neighbourhood structures play a critical role in solving JSP. At present, there are three state-of-the-art neighbourhood structures, i.e. N5, N6, and N7. Improving the upper bounds of some famous benchmarks is inseparable from the role of these neighbourhood structures. However, these existing neighbourhood structures only consider the movement of critical operations within a critical block. According to our experiments, it is also possible to improve the makespan of a scheduling scheme by moving a critical operation outside its critical block. According to the above finding, this paper proposes a new N8 neighbourhood structure considering the movement of critical operations within a critical block and the movement of critical operations outside the critical block. Besides, a neighbourhood clipping method is designed to avoid invalid movement, discarding non-improving moves. Tabu search (TS) is a commonly used algorithm framework combined with neighbourhood structures. This paper uses this framework to compare the N8 neighbourhood structure with N5, N6, and N7 neighbourhood structures on four famous benchmarks. The experimental results verify that the N8 neighbourhood structure is more effective and efficient in solving JSP than the other state-of-the-art neighbourhood structures. [ABSTRACT FROM AUTHOR]

The Robotic Assembly Line Balancing Problem (RALBP) is a joint optimisation problem that is concerned with assigning both assembly operations and robots to workstations that are placed within a straight line. RALBP-2 is the particular problem where the cycle time, which is the maximum time spent on a workstation by the product being assembled, is minimised while the number of workstations is fixed. Sequence-dependent setup times are considered which raises the problem of sequencing the operations assigned to each workstation. Both the durations of the operations and the setup times depend on the robot. Two different variants are identified from literature. The first variant assumes that, given a set of types of robots, each type of robot can be assigned to multiple workstations without any limitation. Given a set of robots, the second variant forces each robot to be assigned to at most one workstation. Both assumptions are studied in this paper. The particular case of a given giant sequence of operations is solved thanks to a polynomial optimal algorithm. The latter algorithm, called split, is then embedded in a metaheuristic framework that explores the space of giant sequences. Benchmark data sets from literature are considered in the experimental section. A comparative study with other methods from literature shows the competitiveness of the suggested approach. [ABSTRACT FROM AUTHOR]

In practical manufacturing systems, the job processing time usually varies with the performance change of manufacturing resources, among which the learning and deteriorating effects are typical characteristics. Due to the interests from both academic exploration and industrial innovation, the research on scheduling problems with these effects is abundant and diverse. However, some studied problems need to be strengthened in combination with realistic production scenarios. This paper provides a concise guide to scheduling problems with these effects, giving a comprehensive review and critical hints for future research. A novel classification scheme is designed based on four levels of different domains, i.e. effects, processing ways, processing time functions, and manufacturing environments. Based on this scheme, the scheduling problems are first distinguished into three categories: learning effects, deteriorating effects, and combined effects. In each category, models are then refined along three lines: general processing way, batch scheduling, and group scheduling. Combined with the attributes of actual processing time functions and manufacturing environments, the evolvement of related scheduling models and a critical analysis on the proposed algorithms are well analysed. Afterwards, the research gaps are revealed and the research directions are indicated from the perspectives of practical applications, time functions, and designed algorithms. [ABSTRACT FROM AUTHOR]

In a complex and dynamic job shop containing logistics factor, schedule needs to be generated rapidly, so the real-time scheduling method is more suitable for such scenario. Such method takes advantage of local information within a short time due to the rapid changes of information under uncertain environment. Therefore, how to make use of the future information by prediction while ensuring the robustness of schedule is a valuable problem. To solve it, firstly, a new real-time scheduling model and algorithm is proposed. There is a new kind of release moment of task information which can give AGVs the longest time to prepare for the task than existing research. Secondly, a real-time information update mechanism is designed to increase schedule's robustness. Finally, a large-scale and dynamic job shop simulation experimental platform is developed. Dynamic factors include the random insertion of orders and failures of equipment. Results show that the method proposed outperforms existing research in terms of customer satisfaction, equipment utilisation and energy consumption. The robustness of schedule can also be acceptable. This paper also finds a rule that in job shop with the large proportion of logistics transportation time, the above method can achieve more competitive results. [ABSTRACT FROM AUTHOR]

Many materials machine in either a ductile or brittle manner depending on the cutting conditions. This paper identifies the conditions which allow perspex to be machined in a ductile manner. A quantitative assessment is made of the effects of cutting speed and feed rate on the ductile-brittle transition when turning with a tool having a 30degrees rake angle. [ABSTRACT FROM AUTHOR]

Recently, industrial and academic communities in the operations and supply chain management (OSCM) field are paying increasing attention to social media. However, the value of social media in OSCM is quite unclear, and more investigations are still needed. To pave the way for directed future research, this paper systematically reviewed and synthesised 152 peer-review journal papers to identify research focus and gaps in this area, supported by an appropriate conceptual framework. The result reveals that the research interests in this area have increased dramatically within the last decade across various industries and regions. Different companies' OSCM activities, such as sourcing and delivery, can benefit from employment of social media. This paper also indicates that future research can explore the value of social media in sourcing, delivery, product return and reverse logistics, forecasting and inventory management, and product development and production. [ABSTRACT FROM AUTHOR]

This paper provides a literature review on zero defect manufacturing based on the content analysis performed for 280 research articles published from 1987 to 2018 in a variety of academic journals and conference proceedings. The review summarises the state-of-the-art, highlights shortcomings and further directions in research. Accordingly, we investigated how zero defect manufacturing was implemented and evaluated the main research patterns in the sample by analysing key factors. Based on the extensive review of the zero defect manufacturing literature, we identified and highlighted four distinctive strategies based on overarching themes for zero defect manufacturing, i.e. detection, repair, prediction, and prevention. Evaluation of current research and descriptive analysis highlighted six major shortcomings of current research in zero defect manufacturing: (i) focus on a single strategy instead of a holistic approach for global optima; (ii) certain industries are under-researched; (iii) full potential of industry-academia collaboration is not achieved; (iv) not enough focus on the beginning of manufacturing lifecycle; (v) cost–benefit comparative analysis is not evident; (vi) standard and clear definition of terms are missing. Finally, we presented four further directions in which an advance of the topic would stimulate scholarly and practical needs: (i) shift from local to global solutions; (ii) investigate pros and cons; (iii) role of people and human activities in manufacturing; (iv) new business models for zero defect manufacturing. [ABSTRACT FROM AUTHOR]

Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment. [ABSTRACT FROM AUTHOR]

Horizontal collaboration has been considered as effective practice for sustainable logistics and freight transport and it has gained increased attention in recent years. This paper aims to provide a survey of the development of horizontal collaborative transport (HCT) over the past ten years, to identify research trends and gaps, then to propose some research opportunities. The paper also aims to provide guidelines to logistics companies who wish to embark on HCT, to help them choose which HCT solution to implement. To provide a comprehensive and structured review, the paper follows the methodology for Systematic Literature Review proposed in the literature. A total of 120 scientific papers published between 2007 and 2017 were reviewed. A survey framework based on two axes – HCT solutions and implementation issues – is developed to analyse and position the papers. The results show that, regarding HCT solutions, carrier alliance and flow controller collaboration were the most frequently studied. But recent innovative solutions such as pooling and physical internet are also gaining increased attention. Regarding implementation issues, the focus of the literature has been on the development of decision-making models, including transport planning, lane exchange, and gain sharing. Conversely, managerial and technological issues have received less attention. [ABSTRACT FROM AUTHOR]

An introduction to articles in the issue is presented on topics including a complementary study that focused on the research methods used in production research, the effects of the "International Journal of Production Research" (IJPR) in its fields of research by comparing IJPR with its top peer journals, and the impact of internet of Things on supply chain management.

The interest of lean companies in tools to monitor and control their lean implementation process, i.e. their leanness level, is continuously increasing. A multitude of diverse approaches have been proposed in the literature for that purpose. In order to provide some guidance both to practitioners interested in selecting a tool and academics aiming at developing a new approach, a systematic review of the methods to measure leanness in manufacturing organisations is carried out. Thirty-one methods are identified and critically analysed based on a set of comparative dimensions. The main strengths and weaknesses of each approach are highlighted. In particular, this paper's results show that only less than a third of the methods are able to assess leanness in a complete way, taking into consideration both the degree of lean practices adoption and the performance outcomes resulting from implementation. In order to contribute to the reinforcement of a unifying view of the leanness concept, a new leanness definition is developed. Some further gaps in the literature are pointed out, providing directions for future research. [ABSTRACT FROM AUTHOR]

The International Journal of Production Research (IJPR) first issue was published in 1961. This year commemorates the journal's 55th year anniversary. In celebration of its anniversary, this article aims to comprehensively review the journals overall existence (1961–2017), per decade, by a longitudinal analysis of the literature through a main path analysis, and a bibliometric and social network overview. This paper differentiates from previous IJPR's studies conducted by focusing on the journal's social network analysis (SNA) by decades and overall period. This research article classifies leading bibliographic material by using the total number of publications, citations, authors per work, country, author's affiliation, funding agencies, keywords, co-authorship and the top-10 cited papers (with objectives and contributions), over the previous five decades. In conjunction with utilising SNA, major findings indicate remarkable improvement on authors' publication due to a strong social network. Furthermore, the results suggest that the improvement of Asian universities on the IJPR is not only a result of a strong social network among authors, but also an active support from national research funding agencies. The collaboration between researchers appears to be evidently rising by an increasing percentage of articles penned by three or more authors and the average number of authors per article published. The main path analysis identifies the 30 milestone papers which constitute the backbone of the knowledge published in the overall IJPR history. [ABSTRACT FROM AUTHOR]

Addressing the materials feeding principle of kitting, commonly applied in the materials supply to mass-customised assembly, the current paper has the purpose of exploring how the man-hour efficiency of kit preparation is affected by the design and the context of the kit preparation. The study presented in the paper is based on a comprehensive methodology, comprising several steps and considering a large set of qualitative as well as quantitative data from 15 case studies. It also utilises the expertise of practitioners from the industry. The paper provides a valuable addition to the existing literature where empirical evidence is scarce. From a practical perspective, it offers support to the design of man-hour efficient kit preparation systems. The findings show that the design and the context of the kit preparation system can have a decisive, yet complex, impact on the man-hour efficiency and, thereby, on an assessment of the applicability of kitting. The paper identifies several important aspects of both design and context and indicates how these aspects are linked to the man-hour efficiency of kit preparation. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate that the relation between two jobs defined by min{ai, bj} ≤ min{bi, aj}, used in Johnson’s theorem, is not transitive. However, both the theorem and Johnson’s algorithm are correct. [ABSTRACT FROM AUTHOR]

When creating a product, a supplier faces the problem of designing the optimal contract to screen the manufacturer's private information. In this paper, we consider a manufacturer with private information about the cost type of production (N types defined in this paper) and its unobservable effort. Aiming to eliminate the negative effects on the green building market development caused by these two kinds of private information, we build a principal-agent model with asymmetric information. The optimal subsidy of the model is obtained by introducing the 'spot check mechanism'. The results show that manufacturers with reasonable subsidies will not defraud the public about the actual quality of green buildings. Moreover, we discuss the impact of the probability of spot checks and subsidies on the optimal solution. Finally, a numerical example is given to show the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Reconfigurable Manufacturing Systems (RMS) emerged from companies' needs to increase their responsiveness to an uncertain market, in which customers are increasingly demanding mass-customised products. Companies focused on mass customisation mainly use the modular product design (MPD) strategy to cost-effectively provide a large product variety. Hence, coupling the MPD with the manufacturing in RMS seems to be a good strategy to effectively provide mass-customised products with lower costs. However, few papers have concurrently optimised the modular products' and RMS's configurations for that end. Further, very few papers have explored the RMS's layout configuration. In order to fill these gaps, this paper proposes a Nonlinear Integer Programming model that integrates the configuration of modular products and RMS, driven by individual customer requirements, to minimise manufacturing costs of mass-customised products. An approach combining a Modified Brute-Force Algorithm (MBFA) and a genetic algorithm (GA) is proposed and compared with a CPLEX-based approach for a small-sized problem, proving its ability to find an optimal solution in lower computation time. An illustrative example of modular smartphones confirms the MBFA-GA's ability to solve medium/large-sized problems in a reasonable amount of time while ensuring an optimal product configuration that meets customer requirements. [ABSTRACT FROM AUTHOR]

Collaborative robots (cobots) are important components of the Industry 4.0 paradigm and smart manufacturing. Cobots are known for their ability to interact with the operators in a shared workspace. Due to their spread in the last decade, cobot research proliferated. However, most individual studies focused on specific aspects of cobot deployment, and only scant attention was given to their evaluation (mostly not based on productivity criteria). Thus, better support is needed for cobot acquisition and deployment decisions. This paper answers this need by presenting a summary of the major considerations related to cobots acquisition and deployment, and providing a productivity analysis procedure that supports cobot acquisition and deployment decisions. Defining the cobots' required characteristics and capabilities, effectively narrows the possible selection of cobots. However, it does not give information as to the economic value of acquiring and deploying a specific cobot. So, in addition to cobots' characteristics and capabilities, this paper presents computational techniques to analyse and support this decision for a single workstation per se, and for a station in an assembly line. The difference between these two cases is discussed and analysed, and corresponding models are presented with computational examples. [ABSTRACT FROM AUTHOR]

This paper conducts a state-of-the-art review for a particular emerging field of Production Research: pricing optimisation, channel and uncertainty. This is achieved by presenting a set of state-of-the-art papers accepted to this special issue, and co-word analysis to trace the development of this research field. Data for co-word analysis is based on literature search in the International Journal of Production Research, since 1961 using Web of Science with the Keywords 'pricing optimization', 'channel' or 'uncertainty'. Pricing approaches and tools have attracted more and more attentions from multiple disciplinary such as supply-chain management and marketing. The objective of this special issue is to contribute new insights to the extant body of knowledge in pricing optimisation, channel and uncertainty, specifically for 55th anniversary of International Journal of Production Research. [ABSTRACT FROM AUTHOR]

This introduction to the special issue celebrates the 30th anniversary of the publication of Sugimori et al. (Sugimori, Y., Kusunoki, K., Cho, F. and Uchikawa, S., Toyota production system and Kanban system: materialisation of just-in-time and respect-for-human system. Int. J. Prod. Res., 1977, 15(6), 553-564), the first extensive description of the Toyota Production System (TPS) to be published in English. After some initial discussion of the TPS, this article reviews three important issues regarding the context of the original paper: the West's growing interest in Japanese manufacturing; the preoccupation with information technology as the future of production; and, concerns with job design and motivation. The Sugimori paper is then analysed in these terms, focusing on the technical and human elements of the TPS. The article closes with an introduction to the other papers in the special issue. [ABSTRACT FROM AUTHOR]

This paper deals with mobile-rack automated storage/retrieval systems (AS/RS) that are a particular physical configuration of unit-deep AS/RS, i.e. the class of systems where each cell is designed to contain a single load. There are two main contributions in this paper: the first one is the analytical modelling of the average single-cycle time for mobile-rack AS/RS. The approach adopted for modelling is based on a continuous approximation, which is not recent, however, the approach proposed here for the transition from the discrete to the continuous models is different from those used previously in the literature. In a certain way, the multi-aisle and unit-load configurations can be seen as special cases of the mobile-rack configuration. This allows to deduce analytical models for the average single-cycle time for these two configurations from the one developed for mobile rack. The second main contribution of this paper is to find the dimensions of the AS/RS that minimise the average single-cycle time. The optimisation has been studied formally for the multi-aisle and unit-load configurations, and numerically for the mobile-rack configuration. [ABSTRACT FROM AUTHOR]

This paper introduces the Cyclic Production Routing Problem (CPRP). The CPRP is an extension of the well-known NP-hard Production Routing Problem (PRP), which is a hard-to-solve combinatorial optimisation problem with numerous practical applications in the field of freight transportation, logistics and supply chain management. Under the PRP setting, a manufacturer is responsible for determining production decisions, as well as the timing and quantity of replenishment services offered to a set of geographically dispersed customers over a multi-period time horizon. The problem calls for jointly optimising the production, inventory, distribution and routing decisions. In this paper, the basic PRP model is modified to generate repeatable cyclic production and delivery schedules. A two-commodity flow formulation is proposed along with valid inequalities. Extensive comparisons between the basic PRP and the proposed cyclic variant on well-known benchmark instances are provided. The new variant is significantly harder to solve, especially when the vehicle fleet is limited. From a managerial perspective, the generation of cyclic production-routing schedules significantly increases all costs, whereas the number of vehicle routes required to implement a cyclic schedule is higher. [ABSTRACT FROM AUTHOR]

Industry 4.0 was presented more than a decade ago as the fourth industrial revolution, aiming to significantly raise the level of sophistication of interconnected technologies and thus increase manufacturing industries' profits. However, because the technology-driven narrow focus of Industry 4.0 on performance and profit fails to explain how to increase prosperity for all the stakeholders involved, the European Commission has introduced the concept of Industry 5.0. This vision overcomes the weaknesses of Industry 4.0 by paying explicit attention to outcomes for humans in the system and establishing an environment to create human-centric, resilient, and sustainable systems. Considering these developments, this position paper and editorial introducing the special issue of the International Journal of Production Research elaborates on the transition from Industry 4.0 to 5.0 through 10 papers focusing on the human-centric pillar of Industry 5.0 and its impacts on production and logistics system design and management. This work presents guidance for a more systemic approach needed in future research: to include empirically grounded works and data-driven multimethod approaches that consider diversity in system operators and human factors demands holistically in order to incorporate ethical implications missing from Industry 4.0 – in the pursuit of Industry 5.0 systems. [ABSTRACT FROM AUTHOR]

Cognitive assistance systems help people with learning disabilities to increase their skills and consequently their employment opportunities in the regular labour market. Research on advanced work instructions has encouraged training disabled workers in cognitively demanding production tasks, especially manual assembly. However, studies lack evidence on the effect of repetition or work cycle alongside the form of instruction and type of disability. This paper addresses this gap and reports on an experiment conducted at a sheltered workplace. Four forms of instruction (paper-based, animations, projection, adaptive projection) were tested to assist operators with three types of disability (illiterate, psychosocial, cognitive) with a manual assembly task. The results show that projection enhances the first assembly cycle. Challenging operators by filtering the content of the instruction with increased experience leads to greater independence and a better understanding of their tasks. However, adaptive instructions can form a barrier for those operators who are most dependent on mentor support. The form of instruction should thus be considered carefully for each operator as their adaptation to changes and cognitive assistance systems varies. The results are discussed in light of the Industry 5.0 human-centric and socially sustainable production agenda with managerial and research implications and future research priorities. [ABSTRACT FROM AUTHOR]

Previous research on automated guided vehicles (AGVs) and Industry 4.0 has mainly focused on technical aspects, while the humans who work with AGVs as well as the influences on the organisation have received limited attention. This paper aims to explore human- and organisation-related challenges in the introduction of AGVs in production facilities. Two cases are examined and analysed using the Human, Technology, and Organisation (HTO) model, which highlights the interactions between the three subsystems: human, technology, and organisation. The paper shows that several human- and organisation-related challenges arise when introducing AGVs, such as supporting the AGVs with new work procedures for managing AGV errors, determining what different operators need to know about AGVs, and developing acceptance among employees. The identified challenges complement the technical focus in previous research. Actions are proposed to facilitate the introduction of AGVs to avoid or manage the identified challenges. The findings of this study can help managers involved in the introduction of AGVs to consider human- and organisation-related aspects to improve AGV performance and employee well-being. [ABSTRACT FROM AUTHOR]

Sales and operations planning (S&OP) has emerged as a planning approach that integrates tactical level decisions across functions and supply chains while aligning day-to-day operations with long-term strategy through these decisions. The extant knowledge on S&OP has evolved primarily based on the needs of mass production contexts, and applications of S&OP in engineer-to-order (ETO) contexts have not been explored by previous research. Arguing that the cross-functionally coordinated planning enabled by S&OP can improve the effectiveness of the challenging and competitively critical tendering process, this paper develops an S&OP framework for the tactical planning process design to support delivery date setting in ETO contexts. The paper adopts a systematic literature review approach for identifying the main tactical planning activities managers in ETO companies should consider while designing the S&OP process and the information inputs required for performing and coordinating these planning activities. The identified planning activities and planning inputs are synthesised to develop the proposed S&OP framework for delivery date setting in ETO contexts. The proposed framework can support managers in assessing which tactical planning activities are strategically essential in their respective companies and redesigning or reconfiguring existing planning processes to address the planning needs of their environment. [ABSTRACT FROM AUTHOR]

Changing customer requirements and turbulent markets require suitably adapted capabilities to proactively cope with rapid changes. Agile manufacturing emerged in the late 1990s as a competitive concept to respond to these business challenges. While several seminal research works address agility in terms of concept definition, drivers and strategic capabilities, there is a lack of implementation frameworks of agile manufacturing. The current paper is concerned with the question of how to improve the agility of manufacturing companies. To address this question, a framework is iteratively developed with the aim of supporting decision makers in planning and implementing agility improvement projects. To this end, Design Science Research (DSR) methodology is used in conjunction with CIMO-logic (Context, Intervention, Mechanism, Outcome). The iterative development of the framework relies heavily on insights from case studies and from practitioners in the broad manufacturing sector. The paper provides evidence of the validity of the framework as well as outlining further research perspectives. [ABSTRACT FROM AUTHOR]

Decision-making in supply chains is challenged by high complexity, a combination of continuous and discrete processes, integrated and interdependent operations, dynamics, and adaptability. The rapidly increasing data availability, computing power and intelligent algorithms unveil new potentials in adaptive data-driven decision-making. Reinforcement Learning, a class of machine learning algorithms, is one of the data-driven methods. This semi-systematic literature review explores the current state of the art of reinforcement learning in supply chain management (SCM) and proposes a classification framework. The framework classifies academic papers based on supply chain drivers, algorithms, data sources, and industrial sectors. The conducted review revealed a few critical insights. First, the classic Q-learning algorithm is still the most popular one. Second, inventory management is the most common application of reinforcement learning in supply chains, as it is a pivotal element of supply chain synchronisation. Last, most reviewed papers address toy-like SCM problems driven by artificial data. Therefore, shifting to industry-scale problems will be a crucial challenge in the next years. If this shift is successful, the vision of data-driven decision-making in real-time could become a reality. [ABSTRACT FROM AUTHOR]

This paper develops an optimal replacement policy V* for a multi-state manufacturing system. The manufacturing system would be repaired imperfectly once its performance cannot meet the production demand, and would be replaced when the production demand is not met for the V*-th time. Due to imprecise state assignments and unpredictable external working conditions, the performance and transition intensity of the multi-state machine cannot be accurately identified and then inevitably lead to epistemic uncertainty. In addition, the economic dependence and resource dependence that prevailed in the manufacturing system should be considered. In this paper, economic dependence is described as the time and cost saved by simultaneously repairing multiple identical machines, and resource dependence is caused by finite capacity buffers. To take these into account, the fuzzy Markov model and fuzzy stochastic flow manufacturing network (FSFMN) are tailored to evaluate the fuzzy reliability of machines and manufacturing systems, respectively. To obtain the optimal replacement policy V*, we derive the expression of the long run fuzzy profit rate under epistemic uncertainty. The replacement policy is demonstrated on the ferrite phase shifting unit manufacturing system, and the results of the subsequent comparative study and sensitivity analysis show that this policy is more effective. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to help online grocery retailers determine the optimal return and refund policies for perishable grocery items. Three refund policies and two return requirements are modelled: no-refund, full-refund and partial-refund, with or without product return. We first derive the optimal refund policy under two scenarios, where either product return is or is not required for refund. We further analyse how market conditions impact the optimal policies. Lastly, we investigate when product return should be required for refund. Our results show that a more generous refund policy should be offered if the product has a higher profit margin, if an unsatisfactory product has a large negative impact on consumer utility, and if consumers have high return costs when product return is required for refund. Our results also show that it is optimal not to require the unwanted product to be returned when consumer's return cost and product return rate are above certain threshold values. This paper fills the gap in the literature on return and refund policies in an online grocery setting. The findings of this paper provide explicit guidance to online grocery businesses on how to optimally determine the return and refund policies. [ABSTRACT FROM AUTHOR]

As assembly systems move into the era of mass customisation, the complexity of design processes, (re)configurations and operations rises. Well-structured data are key in keeping this complexity manageable. Here to, this paper presents a multidimensional formal skill model designed to deliver generic descriptions of needs and capacities with skills as the connector between products, processes and resources. The model formalises resource structures in relation to the processes they master and products they can produce. This paper discusses the case-based evaluation in a reconfigurable assembly system and highlights the added-value of a skill-based modelling approach. The presented formal model combines concepts coming from both offline and online modelling perspectives and allows for various applications and levels of detail. The resource structures embedded in the prerequisites of a skill enable matchmaking of resources for workspace design and reconfigurations. The mapping of the model to standardised ISA-95 models couples production needs to the resources allowing for more optimal production planning, control and a structured interface between enterprise and control systems. The possibility to couple states to the assembly environment allows for optimal runtime orchestration. [ABSTRACT FROM AUTHOR]

Industry 4.0 aims to establish highly flexible production, enabling effective and efficient mass customisation of products. Modelling techniques and simulation of production processes are among the core techniques of the manufacturing industry that facilitate flexibility and automation of a shop floor in the era of Industry 4.0. In this paper, we present an approach to support production process modelling and process model management. The approach is based on Model-Driven (MD) principles and comprises a Domain-Specific Modelling Language (DSML) named Multi-Level Production Process Modelling Language (MultiProLan). MultiProLan uses a set of concepts to specify production process models suitable for automatic instruction generation and execution of the instructions in a simulation or on a shop floor. By using MultiProLan, process designers may create process models independent of the specific production system. Such process models can either be automatically enriched by matching and scheduling algorithms or manually enriched by a process designer via MultiProLan's modelling tool. In this paper, we also present an application of our approach in the assembly industry to showcase its dynamic resource management, generation of production documentation, error handling and process monitoring. [ABSTRACT FROM AUTHOR]

The Industry 4.0 revolution is changing the manufacturing landscape. A broad set of new technologies emerged (including software and connected equipment) that digitise manufacturing systems. These technologies bring new vitality and opportunities to the manufacturing industry, but they also bring new challenges. This paper focuses on the impact of Industry 4.0 on production planning approaches and software. We first propose a digital twin framework that integrates production planning systems and frontier technologies. The frontier technologies that may impact production planning software are the internet of things, cloud manufacturing, blockchain, and big data analytics. Second, we provide a state-of-the-art on the application of each technology in the production planning, as well as a detailed analysis of the benefit and application status. Finally, this paper discusses the future research and application directions in the production planning. We conclude that Industry 4.0 will lead to the construction of data-driven models for production planning software. These tools will include models built accurately from data, account for uncertainty, and partially actuate the decision autonomously. [ABSTRACT FROM AUTHOR]