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This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products. [ABSTRACT FROM AUTHOR]

The rise of mass customisation drives manufacturers to adopt leasing agreements for their machinery rather than outright their ownership. This industrial trend results in large-scale leased manufacturing systems, where the asset conditions and maintenance requirements for a fleet of machines and/or production lines from several manufacturers are continuously monitored and managed by a lessor. In this paper, we propose an operations and maintenance planning model that explicitly models (i) dynamic real-time failure rate predictions for machines based on sensor-driven degradation data, (ii) optimal routes for maintenance teams across a number of geographically-distributed manufacturing sites, and (iii) operational outcomes. The model can handle complex maintenance and operational outcome interdependencies between multiple machines, and incorporate demand for different products, heterogeneous machine capacities and capabilities, factory topology, and the resulting production flow capacities of products. To demonstrate the model's practicality, it is applied to three experimental case studies with various numbers of machines, operating schedules, product types, and flow capacities. The results show that the proposed model significantly outperforms the traditional reliability-based maintenance model in key metrics such as the number of unexpected failures, the cost of preventive maintenance actions, machine downtime, the percentage of unsatisfied demand, and total cost. [ABSTRACT FROM AUTHOR]

This paper constitutes a comparative assessment of the impact of robots on local labor markets across eight European countries. Doing so, we find that robots generally reduce employment in the manufacturing sector, while their impacts on total employment are more ambiguous. Though local markets experienced significant employment losses in Italy, Norway, and the United Kingdom, we find no statistically significant impact of robots on employment in Germany, Sweden, Denmark, Finland, and Spain. Job losses were seemingly offset by employment gains in other sectors of the economy. We explore two mechanisms that might explain these patterns: differences in investment in complementary job-creating technologies and robot-induced reshoring. Our analysis provides some support for both mechanisms in elucidating the differential impacts of robots on jobs across space. [ABSTRACT FROM AUTHOR]

In the servicization business model, a service-oriented manufacturer sells the service derived from its products. Because of the special compensation method, a service-oriented manufacturer is more likely to be underfunded. A Stackelberg game is formulated to investigate the interaction among a bank, a manufacturer, and an operator, in which two financing strategies are considered: bank financing and guaranteed (internal) financing. The difference between these two strategies is who bears the bankruptcy risk of the manufacturer. With bank financing, the bank bears the risk and determines the interest rate, while under guaranteed financing, the operator sets a guaranteed financing interest rate. We find that under bank financing, the low operating efficiency of the manufacturer increases the bank's share of the supply chain benefits. In particular, the service-oriented manufacturer can rarely be financed if the bankruptcy risk is high. However, under guaranteed financing, the operator may, interestingly, even subsidise a manufacturer with high operating efficiency. In this situation, a high bankruptcy risk could incentivize the manufacturer to improve its operating efficiency for the sake of the subsidy. Practically, guaranteed financing could coordinate the supply chain through interest rate adjustments or subsidies when facing different risk levels, which could improve both firms' benefits. [ABSTRACT FROM AUTHOR]

This paper proposes a service-oriented manufacturing strategy in a two-echelon supply chain with random demand. When there is no inventory for the retailer to meet demand, customers can choose to order products through the retailer and products will be delivered to them by the manufacturer directly in the promised time, and we call this delivery service in service-oriented manufacturing. We employ a Stackelberg game-theoretic model to analyse the procurement quantity and delivery time decisions by the manufacturer as the leader and the retailer as the follower. Using the performance of the pure-manufacturing strategy as a benchmark, our main results follow. First, the equilibrium strategies of the two players are obtained. Clear decision rules are also given. Second, delivery service in service-oriented manufacturing can be an effective way to reduce the holding cost of the retailer. Third, we describe the customer loss caused by waiting and find how the manufacturer influences procurement quantity of the retailer through the decision of delivery time. Finally, delivery service in service-oriented manufacturing cannot always improve the profit of the manufacturer and the retailer. We give guidance for managers to provide it. [ABSTRACT FROM AUTHOR]

This paper explores the optimal homing policy of a manufacturer who sells products through two competing platforms: a traditional online platform and a social commerce platform. The social platform can choose to operate with reselling or agency selling format. Through analysis, we first find that the manufacturer's optimal decision regarding whether to single- or multi-home and the social platform's optimal decision regarding whether to adopt reselling or agency selling format depend mainly on the intensity of the downstream competition and the platforms' market sizes. Specifically, the manufacturer prefers single-homing if the competition intensity is relatively low and the traditional platform's market size is relatively large. When the competition intensity increases (decreases), the agency selling (reselling) format is always the social platform's preferred choice. Next, we find that the manufacturer is less likely to choose multi-homing (single-homing) and the social platform is more likely to select agency selling (reselling) format when the traditional platform serves as a marketplace rather than a reseller. Finally, numerical studies show that the manufacturer's and the platforms' preferences for selling modes are always misaligned. However, an all-win situation is achieved with the pure agency selling mode when the competition intensity is relatively high. [ABSTRACT FROM AUTHOR]

As a manufacturing power in the era of Industry 4.0, the Chinese traditional manufacturing industry urgently needs innovation and upgrading. In this process, the pressure on the traditional manufacturing industry is mainly financial shortages. The government can act as a Booster to add power to the upgrading by providing financial support. We build a three-tier game model consisting of Raw Material Suppliers, a Traditional Manufacturer, and an Original Equipment Manufacturer to explore the upgrading conditions and construct three settings: Agency, Consignment, and Design. We find that the government subsidy can serve as an effective way to ease enterprises' financial burden and improve the innovation level, which is more evident when the traditional manufacturer innovates. In addition, when the market competition and the government subsidy are both at a moderate level, the combined effect of the two factors is positive, and the condition is the best to upgrade. Encouragingly, the social welfare under Design will be the highest when the government subsidy is slightly great. Finally, excessive subsidy hinders upgrading and aggravates market competition, even if the traditional manufacturer enjoys exorbitant profits. HIGHLIGHTS The upgrading on the manufacturing industry in the era of Industry 4.0 The right of product design in supply chain models The cross-influence of the government subsidy and market competition on industrial upgrading is introduced The conditions to help upgrade the manufacturing industry are given in the era of Industry 4.0 [ABSTRACT FROM AUTHOR]

Compared to the traditional channel, where a retailer bears the inventory risk, the drop-shipping channel operates with a distinct approach: the retailer avoids stocking products while the manufacturer directly handles stocking and shipping to consumers. Due to the different inventory risk allocations, the two channels have different product qualities and profits for the manufacturer and retailer. In this study, we investigate product quality decision of the manufacturer and delve into the impact of product quality on the manufacturer's and retailer's profitability. First, we find that product quality can be weakly higher in the drop-shipping channel than that in the traditional channel. This is because the drop-shipping channel allows the manufacturer who undertakes demand uncertainty to charge a higher wholesale price, resulting in a higher product quality. Second, our study reveals that the traditional channel can concurrently yield higher profits for the manufacturer and retailer when product quality is considered, which is in contrast to the previous works. Third, in the traditional channel, as demand uncertainty rises, the retailer's production quantity increases, while the manufacturer's product quality decreases. Finally, our results indicate that the product quality is more sensitive to the shipping cost when demand uncertainty is low. [ABSTRACT FROM AUTHOR]

We consider a manufacturer and an e-platform where the manufacturer sells products through offline and e-platform channels under the cap-and-trade scheme. The interaction between the two channels produces the cross-channel effect (CCE). This manufacturer cooperates with the e-platform in the agency or reseller mode. In addition, the platform shares its observed data with the manufacturer and the blockchain can achieve traceability and high transparency of these data. We formulate a Stackelberg game to derive the following results: In the agency mode, the optimal service level is independent of (decreases with) CCE without (with) blockchain. CCE positively affects the optimal service level in the reseller mode and the optimal service level has no impact on (increases with) the cap in the agency (reseller) mode. Second, when the platform-enabled power is high (low), the platform is (not) willing to adopt blockchain. Third, coordination of the manufacturer and platform only can be achieved in the agency mode when CCE is low with blockchain. The reseller mode can (cannot) achieve coordination of the two firms with (without) blockchain. We also consider the cases where the manufacturer serves as the leader and the omni-channel strategy is adopted to check the robustness of the coordination results. [ABSTRACT FROM AUTHOR]

In modern manufacturing and service industries, urgent orders and service tasks are common, and the speed of handling such urgent tasks is an important indicator of production and service efficiency. In this study, we consider scheduling jobs on two parallel machines with the random arrival of an emergency job. The objective is to minimise the makespan, subject to a given maximum waiting time of the emergency job. We first show that the worst-case ratio of the existing algorithm LPT $ _l $ l -SPT $ _{m-l} $ m − l is at least 3/2 when m = 2. We then analyse some properties of the optimal schedule and derive lower bounds on the optimal makespan. Finally, we present an improved approximation algorithm with a tight worst-case ratio of 4/3. We also provide numerical results showing that our proposed algorithm outperforms algorithm LPT $ _l $ l -SPT $ _{m-l} $ m − l . [ABSTRACT FROM AUTHOR]

This paper revisits the ongoing discussion on the concept of industrial relatedness by applying it to manufacturing industries in urban areas. The analysis uses a sample of firms operating in the Brussels Capital Region area and observed over the period 2009–2015. Based on a two-step quantile regression, results show that industrial relatedness is the agglomeration force that mostly sustains the performance of urban manufacturing, whereas this is not the case for other types of agglomeration externalities. Moreover, among the measures of industrial relatedness, the input–output relationship matters more than product similarity in the perspective of a relocation of manufacturing firms in urban areas. [ABSTRACT FROM AUTHOR]

The outbreak of the Covid-19 pandemic led to restrictions in production worldwide. Numerous firms were affected and unable to keep up production due to lockdowns. In disruptive events like this, the resilience of the production system is of central importance, as the survivability of the entire firm depends on it. In this context, the literature argues that cutting-edge technologies, such as Artificial Intelligence (AI), raise the proactive and reactive capabilities of firms, enabling them to better resist and recover from disruptive events and thus, show a higher resilience. This paper takes up this topic and observes the Covid-19 pandemic with the aim to analyse whether a firm's AI-readiness had an impact on its production resilience during the spring 2020 lockdown in Germany. For this purpose, we combine two large-scale surveys containing data from 237 manufacturers in Germany and test hypotheses based on quantitative analyses. Our results show that firms could indeed benefit from AI-enabled production during the lockdown. However, it is also clear that manufacturers have to exceed a certain AI threshold to significantly increase their resilient capabilities and realise positive effects. Our findings not only hold implications for research, but also provide recommendations for the resilience management of manufacturers. [ABSTRACT FROM AUTHOR]

Energy efficiency has become a major concern for manufacturing systems, due to industry being the largest user of scarce, finite energy sources, and also to recent events which have pushed energy prices to alarming levels. In the present Industry 4.0 context, Reconfigurable Manufacturing Systems (RMS) are therefore one of the most promising manufacturing paradigm. In this paper, we investigate the suitability of one of the most common types of RMS, the Parallel-Serial manufacturing line with Crossover, to help minimise the peak of the electric power consumption. More specifically, the balancing of such a production line is studied, so as to integrate power peak minimisation from the design stage. Thus, we define the Parallel-Serial-with-Crossover Assembly Line Balancing Problem with Power Peak Minimization, a new combinatorial NP-hard problem. We also propose a suitable time-indexed Integer Linear Program that integrates balancing and scheduling decisions and a matheuristic algorithm designed to tackle large-size instances. Both approaches are tested on a wide set of instances. The computational results show that relevant power peak reductions can be achieved (33% on average), opening up promising perspectives from both algorithmic and managerial viewpoints. [ABSTRACT FROM AUTHOR]

Rapid advances in new-generation information technologies have been the main driving force for the transformation of manufacturing enterprises in Industry 4.0. Digital twin (DT), as a key technology to promote intelligent manufacturing, has shown great potential for manufacturing enterprises to create an industrial intelligence-driven production equipment through in-depth integration of cyber-physical systems. However, the lack of a systematic effective DT modelling method with a supporting evaluation metric is the most important factor restricting the application of DT in manufacturing enterprises. To bridge the gap, this paper proposes a novel multi-level modelling and fidelity evaluation (MLM&FE) method of DT for creating smart production equipment in manufacturing enterprises, which could help enterprises establish an industrial intelligence-driven production environment to quickly respond to changes in the customised global market, thus greatly improving competitiveness of the enterprises. Specifically, this paper firstly designs a reference framework for DT-enhanced smart production equipment, on which an MLM&FE architecture is proposed. Then, key implementation methodologies and tools for MLM&FE are introduced from the perspective of data space modelling, virtual space modelling, knowledge space modelling, model integration and evaluation. Finally, the developed smart production equipment prototype demonstrates the feasibility and effectiveness of DT MLM&FE. [ABSTRACT FROM AUTHOR]

Yes. We show that aggregate stock returns predict aggregate U.S. employment, despite the industrial composition of publicly traded firms differing markedly from that of all firms, and the representativeness of public firms declining over time. We also show that appropriately reweighted stock returns predict industry and local labor market outcomes. We find the strongest evidence of an alignment of interests between shareholders and workers in the manufacturing sector, despite its declining labor share of output. Our findings suggest that at quarterly frequencies, product demand shocks are more important drivers of industry- and city-level stock returns than technology shocks. [ABSTRACT FROM AUTHOR]

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The COVID-19 pandemic's impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research. [ABSTRACT FROM AUTHOR]

Consumers' perception of product value when purchasing is a critical issue relative to online platform commerce. This is especially true when the brand manufacturer authorises only a third-party reseller to sell through the platform, a practice that may provide opportunities to counterfeiters. To address this issue, we establish a theoretical model in which one brand manufacturer wholesales its products to a third-party reseller who then sells through an online platform. The platform acts as a marketplace, while multiple counterfeiters also exist on the platform, which may deceive consumers. In particular, we consider that the manufacturer can encroach with a direct channel and that the platform can adopt blockchain technology to help consumers identify authenticity. The results show that the platform could induce the brand manufacturer to encroach by deploying blockchain technology. Furthermore, an interesting result indicates that although either manufacturer encroachment or blockchain technology used alone can effectively boycott counterfeits, the coexistence of two strategies can raise the demand for counterfeit products. Finally, we find that when the brand manufacturer encroaches on the platform and the platform adopts blockchain technology, the brand manufacturer, platform, reseller and social welfare can achieve Pareto improvement, while the consumer surplus may be worse off. [ABSTRACT FROM AUTHOR]

Supply chain viability (SCV) is associated with systematic and dynamic approaches to responding to COVID-19 disruptions. The supply chain has been disturbed due to the recurrent nature of the pandemic. In the post-pandemic era, large and small- and medium-sized manufacturers have both advantages and disadvantages, complementing each other. This study proposes an agent-based model to simulate the viable situation of heterogeneous supply systems by considering three behavioural rules (i.e. cooperation establishment, win-win cooperation, and cooperation priority). The results demonstrate that the viability will be improved if large manufacturers cooperate closely with small- and medium-sized manufacturers. The viability is also associated with two adjustment parameters of production capacity, indicating that large manufacturers need to become more scalable, flexible, and adaptable to survive a rapidly changing environment. In addition, when the cooperation is more widely-connected, the viability will be higher. When facing severe fluctuations, large and small- and medium-sized manufacturers can cooperate, acting as a 'sponge system' to flatten the fluctuations. Finally, the simulation results of an empirical network also support this conclusion. Therefore, we suggest that a viable supply chain design should consider integrating supply resources to improve the overall viability of the supply system. [ABSTRACT FROM AUTHOR]

For one-of-a-kind production (OKP) manufacturers adopting an engineer-to-order or make-to-order marketing strategy, it is very important to set an appropriate due date. We design an incentive-compatibility due-date quotation procedure to help OKP manufacturers obtain the rational due-date quotation from OKP customers. Based on the rational due-date quotation decision-making, the performance of an OKP shop floor controlled by load-based pull systems is evaluated in simulation. Our findings show that if the collaboration of due-date quotations and load-based pull control is effective, the order profit of OKP manufacturers will not be reduced when the delivery delay occurs. This study can provide more insights on order quotation decision-making and pull production control for OKP manufacturers. [ABSTRACT FROM AUTHOR]

We examine the manufacturer's encroachment strategy in the supply chain in the presence of the retailer's in-store service. The manufacturer has the option of encroachment with a direct channel, and the retailer has the option of providing in-store service. If the retailer decides to offer service, it sets the service level. We show that in the presence of in-store service, the manufacturer is less likely to encroach on the retail market than in the absence of in-store service. The retailer always prefers to provide in-store service. If the manufacturer decides to encroach, it will strategically use its direct channel with no sales as a threat to the retailer, independent of whether or not the retailer provides in-store service. The retailer can be better off with manufacturer encroachment, but it can be worse off when consumer sensitivity to in-store service is very low. We show that the retailer can strategically employ in-store service to deter the manufacturer's encroachment when the consumer sensitivity to in-store service is sufficiently high. [ABSTRACT FROM AUTHOR]

When does pay dispersion elicit positive or negative employee attitudes? A review of the pay dispersion literature indicates a controversy around this vital question and suggests that numerous contingency factors moderate the effects of pay dispersion. In an empirical study of four Finnish companies consisting of 141 work units, we examine contingencies in attitudinal reactions to job‐based pay dispersion among blue‐collar workers. Based on archival pay data matched with employee survey responses (n = 536), we find that perceptions of pay basis legitimacy, task interdependence, and an individual's pay standing within the work unit explain the strength and direction of the relation between job‐based pay dispersion and employee attitudes (i.e., work engagement and organizational commitment). Our findings have implications for the design of pay systems and contribute to a better appreciation of the complexities underlying employee attitudinal responses to pay dispersion. [ABSTRACT FROM AUTHOR]

After decades, dialogues on human resource management (HRM), intellectual capital (IC), and ambidexterity still continue, mirroring that the role of ambidextrous capability in translating the impact of HRM into superior performance remains unclarified. At this juncture, the current study proposes a novel theoretical framework to extend research on the relationship between IC‐enhancing HR practices and innovation. It is done sophisticatedly by examining how firm exploitative and exploratory capabilities mediate the relationship between different combinations of HR configurations and firm innovation. To this end, we designed rigorous time‐lagged research with three waves of data collection from the Iranian healthcare sector. Our analyses revealed that firm explorative and exploitative capabilities significantly mediate the relationship between human, social, and organizational capital‐enhancing HR configurations and firm innovation. More conspicuously, by unraveling interaction patterns among distinct HR configurations, our study revealed the intricacies of the functioning of IC‐enhancing HR practices in fueling firm ambidexterity. Hence, our study offers design options to navigate through exploitation and exploration in light of the firm's core innovation strategy. We discuss the theoretical and practical implications of our findings and suggest future research avenues. [ABSTRACT FROM AUTHOR]

Contributing to the literature on positive effects of overqualification, this research examines when and why perceived overqualification predicts affiliative and proactive performance at work. Integrating optimal distinctiveness theory with self‐construal theory, we propose that depending on the nature of an employee's self‐construal (i.e., independent, or interdependent), perceived overqualification will be associated with two opposing motivational processes—namely, differentiation and assimilation. We expect perceived overqualification to have a positive relationship with a motive for assimilation when an employee has a strong interdependent self‐construal. Conversely, we expect perceived overqualification to have a positive relationship with a motive for differentiation when an employee has a strong independent self‐construal. We further argue that assimilation‐seeking and differentiation‐seeking motives will be positively related to affiliative and proactive performance, respectively. We conducted two multi‐waved and multisourced studies to test our hypotheses. In a pilot study (N = 249), we first tested our moderation hypothesis. In our main study (N = 496), we tested our overall moderated mediation model. Results from both studies reveal that perceived overqualification can trigger a need for differentiation or assimilation in employees depending on the nature of their self‐construal. The differentiation‐seeking motive was positively related to proactive performance, while the assimilation‐seeking motive was positively related to affiliative performance. Our findings advance overqualification and motivation literatures and provide insights into talent acquisition and management. [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]

Industry 4.0 concepts make it possible to rethink human resources allocation, even for more traditional environments like metal machining. While parts machining on Computer Numerical Control (CNC) machines is automated, some manual tasks must still be executed by operators. The current approach is typically that operators are statically allocated to one or many machines. This causes avoidable bottlenecks. We propose an optimisation model to dynamically assign tasks to the operators with the objective of minimising production delays. Three different scenarios are compared; one representing the current widely used static allocation method and two others that allow more flexibility in the operators' allocation. The dynamic task assignment problem is solved using a constraint programming model. The model was applied to a case study from a high-precision metal manufacturing job shop. Experimental results show that switching from a static allocation to a dynamic one reduces by 76% the average production delays caused by human operators. Supposing more versatile operators under the dynamic allocation leads to further improvements. [ABSTRACT FROM AUTHOR]

Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and human-centricity at its core. Therefore, we propose an architecture that integrates Artificial Intelligence (Active Learning, Forecasting, Explainable Artificial Intelligence), simulated reality, decision-making, and users' feedback, focussing on synergies between humans and machines. Furthermore, we align the proposed architecture with the Big Data Value Association Reference Architecture Model. Finally, we validate it on three use cases from real-world case studies. [ABSTRACT FROM AUTHOR]

There is a powerful global trend toward deeper integration of digital twins into modern life driven by Industry 4.0 and 5.0. Defense, agriculture, engineering, manufacturing, and urban planning sectors have thoroughly incorporated digital twins to great benefit across their respective product lifecycles. Despite clear benefits, a digital twin framework for health and medical sectors is yet to emerge. This paper proposes a digital twin framework for precision neuromusculoskeletal health care. We build upon the International Standards Organization framework for digital twins for manufacturing by presenting best available computational models within a digital twin framework for clinical application. We map a use case for modeling Achilles tendon mechanobiology, highlighting how current modeling practices align with our proposed digital twin framework. Similarly, we map a use case for advanced neurorehabilitation technology, highlighting the role of a digital twin in control of systems where human and machine are interfaced. Future work must now focus on creating an informatic representation to govern how digital data are passed to, from, and within the digital twin, as well as specific standards to declare which measurement systems and modeling methods are acceptable to move toward widespread use of the digital twin framework for precision neuromusculoskeletal health care. [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]

Customer demands force manufacturing companies to offer individualised products to remain competitive. This results in a demand for flexibility and adaptability in product development and production, which causes a rise in complexity. Simultaneously, manufacturers strive to further automatise production and assembly lines to increase cost efficiency and optimise output. This leads to a conflict of interest between two different approaches, 'streamlined and cost-efficient' or 'individualised and costly'. Software-Defined Manufacturing (SDM) is a new approach that seeks to reconcile these diametrical goals by increasing the adaptability of automated manufacturing. This is achieved by virtualising key functionalities of production machines, which permit the configuration of system functionality via software. With current production equipment, this is difficult, because it was designed for a specific process and because there is no meaningful separation between the executing physical part of the machine and the controlling software. This article presents a new method for the development of SDM-ready production machines and processes. The application of the method on a production use-case demonstrates its usefulness in the improvement of existing production facilities and processes. It further addresses the wider trend of Software-Defined Anything (SDx) and outlines the role SDM could play on the pathway towards autonomous manufacturing. [ABSTRACT FROM AUTHOR]

Split thickness skin grafting is one of the common skin transplantation techniques employed in treating severe burn injuries. Recent experimental studies have shown that the expansions offered by split thickness skin grafts are much lower than what is claimed by the graft manufacturers. To date, limited studies have investigated the effect of slit patterns on the expansions and the possibility of material innovation. This work has experimentally tested novel auxetic slit patterns on a biofidelic skin simulant to evaluate their effect on skin graft expansion. A wide range of variants of alternating slit (AS), I-shaped (IS), and Rotating Triangle (RT) based auxetic patterns were tested. A biaxial testing device was employed to simulate realistic skin stretching during graft implementation. The deformation, expansion, stress-strain response, void area, and maximum gap size were estimated, and the material behavior was also modeled using hyperelastic curve fit coefficients. The key design parameters were determined, which would produce high expansion with minimal voids. The findings of this study are anticipated to throw light on the possibility of using auxetic slit patterns for generating higher expansions in split thickness skin grafts. [ABSTRACT FROM AUTHOR]

Based on the application of the stochastic frontier analysis (SFA), this article examines the impact of digital services trade restrictiveness (DSTR) on the total export efficiency and domestic value-added (DVA) export efficiency of manufacturing industries in 46 economies from 2014 to 2019. Results show that DSTR in exporting economies have a negative impact on all types of export efficiency, whereas DSTR in importing economies have a negative impact solely on the efficiency of total exports and final goods exports. Further researches indicate that the impact of DSTR is mitigated in exporting economies with larger information and communication technology (ICT) infrastructures, such as international bandwidth and mobile cellular. From the perspective of multiple policy areas, the DSTR of infrastructure connectivity, electronic transactions, and other barriers reduce the total export efficiency. However, only the DSTR of these areas in exporting economies significantly affect DVA export efficiency. Overall, our findings can inspire economies to adopt more precise and scientific trade policies while participating in the governance of digital services trade and supporting the growth of higher-quality manufacturing exports. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are the air pollutants emitted from the petrochemical industry known to pose adverse health effects on workers. The database based on the third phase of The Environmental Health Study in the Korean National Industrial Complexes (EHSNIC) in Ulsan conducted from 2018 to 2021 was used. Subjects were divided into the exposed and control group according to the estimated pollution level and distances from the industrial complexes. Ambient benzene, ethylbenzene, and xylene were significantly higher in the exposed group compared to the controls, as well as their metabolites. Risk of chronic disease and atopic dermatitis was higher in the exposed group which was supported by higher serum inflammatory markers and high hazard index of the exposed region. These results can draw attention to people engaged with environmental plans and used as primary data when making policies to reduce pollutant levels around industrial complexes. [ABSTRACT FROM AUTHOR]

Airlines select an aircraft's engine simultaneously while purchasing the aircraft. Usually, an aircraft model has multiple engine options, but recently the number of engine options has been decreasing. We develop a three-echelon supply chain model including engine manufacturers, aircraft manufacturers, and airlines to analyze the engine options in airlines' new aircraft purchases. We show that given an airline's existing fleet composition, larger fleet size and higher aircraft production efficiency would make it more likely to choose multiple engine options. In contrast, higher production costs and engine substitutability would lead to a shift to a single engine or hinder the airline's fleet expansion. In the model, we highlight the impact of MRO (Maintenance, Repair, Overhaul) costs with economies of scale on airline engine option decisions as well. In particular, our theoretical findings suggest that the airline would buy more aircraft that are the majority types in their existing fleets, thus crowding out the minority ones. Our findings provide a reasonable explanation for the homogeneity of engine options and provide policy implications regarding airline expansion and aviation supply chain development. • We develop a three-echelon supply chain model to analyze the engine options in airlines' new aircraft purchases. • Larger fleet size and higher aircraft production efficiency would make it more likely to choose multiple engine options. • Higher production costs and engine substitutability would lead to a shift to a single engine option. • Airlines would buy more aircraft that are the majority types in their existing fleets. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to assess the fit of interim crowns produced using DLP‐based 3D printing with different manufacturing workflows—open and proprietary—versus milling technology. Methods: A total of 120 crowns were evaluated using the replica technique. The control group (Mill, n = 30) was manufactured via subtractive technology. Experimental groups were printed using a DLP printer (SprintRay Pro95). In the proprietary mode (SR100, n = 30), manufacturer resin was used with a 100‐μm layer thickness (LT) and a splashing cleaning postprocessing. In the open mode, validated resin was used. Group B100 (n = 30) had a 100‐μm LT, and group B50 (n = 30) had a 50‐μm followed by postprocessing in an ultrasonic bath with full immersion in isopropyl alcohol. Kruskal–Wallis tests with Bonferroni correction was applied after normal analysis (α = 0.05). Results: Group B50 exhibited the best overall fit (123.87 ± 67.42 μm), which was comparable to the gold standard Milling group, which demonstrated the lowest marginal fit (p = 0.760). SR100 showed significantly poorer performance compared to Mill, B50, and B100 (p < 0.001). Conclusions: 3D printed and milled interim crowns generally demonstrated clinically acceptable fit, with the exception of the SR100 group. Postprocessing notably influenced crown fit, with the open mode with total immersion in isopropyl alcohol being superior. Clinical Significance: The present study demonstrates that the selection of an optimal manufacturing and postprocessing workflow results in superior fit for interim crowns. This enables dental professionals to evaluate protocols and ensure reliable outcomes with improved clinical outcomes in interim crown fabrication. [ABSTRACT FROM AUTHOR]

The advancement of the intelligent manufacturing industry (IMI) represents the future direction for the world's manufacturing sector, offering a promising avenue to bolster national competitiveness and enhance industrial manufacturing efficiency. In this study, we took the industrial robot industry (IRI) as a case study to elucidate the spatial distribution and interconnections of IMI from a geographical perspective, and the modified diamond model (DM) was used to analyze the influencing factors. Results show that: 1) the spatial pattern of IRI with various investment attributes in different industrial chain links is generally similar, centered in the southeast. Key investment areas are in the east and south. The spatial distribution of China's IRI covers a multitude of provinces and obtains different scales of investment in different countries (regions). 2) The spatial correlation between foreign investors and China's provincial-level administrative regions (PARs) forms a network, and the network of foreign-invested enterprises is more stable. Different countries (regions) have distinct location preferences in China, with significant spatial differences in correlation degrees. 3) Overall, the interaction of these factors shapes the location decisions and correlation patterns of industrial robot enterprises. This study not only contributes to our theoretical knowledge of the industrial spatial structure and industrial economy but also offers valuable references and suggestions for national IMI planning and relevant industry investors. [ABSTRACT FROM AUTHOR]

The growing use of bacteriophages in the fields of agriculture, agri-food, veterinary treatments, and medicine involves the quantitative production of these bacteriophages. In this study, we propose a bacteriophage production protocol that can easily be transposed to industry. We used a cellstat production system because the latest studies have shown that it is the most suitable process for the production of phages due to volumetric productivity, safety (limitation of co-evolution), and flexibility (choice of growth rate criteria). Sizing of the assembly used makes it possible to extrapolate the results to industrial production. The production conditions are indicated precisely, which would allow manufacturers to adapt the protocol to their own equipment. We propose experimental conditions in order to obtain a stable Escherichia coli population, qualitatively and over time, and production of high-titer T7 bacteriophages. The optimized production conditions (yield, cost and simplicity of the process) are: a buffered peptone water medium concentration of 11 g L−1 and a dilution rate of 1.6 h−1. Under these conditions, we obtained a production of 7.35×1016 plaque-forming units (PFU) L−1 day−1 with a concentration of 9.8×1012 PFU mL−1. The strength of this work lies in its focus on industrial applicability. [ABSTRACT FROM AUTHOR]

In the recent years, Additive Manufacturing (AM) has become a very demanding process utilized by majority of the manufacturing industries due to its complex geometrical capabilities, high accuracy, minimal material usage and better build quality. Among the various types of AM methods, Direct Metal Laser Sintering (DMLS) is a feasible method with many applications and a lot of scope for research. This paper focuses on optimizing the important parameters of DMLS process for better build quality of AlSi10Mg Aluminium alloy. The parameters identified are laser power, hatch distance, scanning speed, and layer thickness. Grey–Taguchi multi response optimization method has been used. Experimental specimens were fabricated and tested. Micro-Vickers hardness and average surface roughness were studied. Experiments were analyzed to determine the best combination of parameters of the DMLS process. A detailed micro-structural study was conducted on the specimens. Also, crystallographic study was made. The resultant specimen thus produced had a better build quality along with satisfying micro-structural characteristics. [ABSTRACT FROM AUTHOR]

This article investigates the effect of various fillets on the performance characteristics of relay electrical contacts. Finite element modeling (FEM) of a relay electrical contact is designed in 3D using the COMSOL Multiphysics simulation tool. Copper material is assigned to the electrical contact pairs. Analysis is carried out for the heights of 0.5 mm and 1 mm. Also, the structure of the contact surface is fine-tuned by using different fillets of 1.5 mm, 1 mm, and 0.5 mm. The voltages of 1 V–10 V are offered, and their performance is evaluated. The key parameters to design the contacts are identified. The electrical, thermal, and mechanical analysis is carried out. The parameters such as current density, contact interface temperature, stress, and pressure are simulated using FEM. The results present the evaluation of relays with different heights through different fillets in various voltage ranges. The results demonstrate that the low fillet radii have a higher contact area and exhibit low current density, low contact pressure, and low stress, which is more reliable and efficient. This study will be highly beneficial for relay and circuit breakers manufacturers. [ABSTRACT FROM AUTHOR]

In this study, we fill the gap of limited effort on systematic literature review into the field of digital technology for occupational health of manufacturing industries. Upon reviewing 53 publications selected by combined bibliometric and classical review methods, we present an integrated overview of the major research areas and hot topics and critically identify the prevalent digital technologies and application modes, the enablers and barriers to implementation, as well as the research agenda in the field of digital technologies in occupational health. The results show that, with the increasing popularity and penetration of digital items like wearable devices and sensors, human–robot collaboration, deep learning analytics, the identified enablers to digital technology implementation are: intelligent manufacturing, competitive condition, data-driven decision-making tool, considerations of welfare and health; and the barriers are: technological gap, privacy and data security, culture and acceptance, and cost consideration. Additionally, propositions on three aspects and six perspectives are recommended for future research in this field. Overall, this study provides insights through systematic analysis and synthesis, and offers the means to achieve Sustainable Development Goals (SDGs) by exploring efficient digital technologies to protect labor rights and improve occupational health in the manufacturing industries.Article Highlights: In-depth analysis of multi-perspective influence of digital technology in occupational health. Synthesis application of bibliometric and classical review methods to identify hotspots, enablers and barriers. Exploring and detailing digital technology’s potential in occupational health for both researchers and companies. [ABSTRACT FROM AUTHOR]

Although innovation patterns under industry life cycle have been investigated for decades, the impact of change in innovation patterns on firm performance has yet to be fully uncovered. This study empirically verifies the impact of product and process innovation on firm performance by considering industry maturity through hierarchical regression analysis using data from the Korean manufacturing industry. Two different measures for firm performance are utilised: innovative product sales and total sales. The results show that both product and process innovation have positive effects on innovative product sales, and industry maturity negatively moderates the positive effect of product innovation on innovative product sales. However, the moderating effect of industry maturity on the relationship between process innovation and innovative product sales is not significantly verified. Moreover, although the direct effect of product and process innovation on total sales is not significantly verified, total sales tend to decrease as the industry matures. Industry maturity positively moderates the effect of process innovation on total sales, while the moderating effect of industry maturity on the relationship between product innovation and total sales is not significantly verified. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to evaluate the effectiveness of a policy, the 2014 UK Supply Chain Plan, which aimed to create a local supply chain in a sector (offshore wind) where the central manufacturing node capabilities and knowledge are not possessed locally. It aims to address the following question: can policy create a new manufacturing supply chain from a void? Design/methodology/approach: A qualitative field research approach is used to derive an original set of theoretical propositions explaining the motivation behind the Supply Chain Plan policy. The outcomes of this policy are examined 10 years later in order to provide an opportunity to observe the impact of the policy. Findings: The conclusion is that the policy has been successful in increasing local content, and some of that local content has benefited local manufacturers. However, a lot of the increase in local content has been achieved in non-manufacturing areas or in new areas. The main issue, i.e. the lack of a central manufacturing capability, remains unaddressed. The impact of the local content policy on cost is undocumented. Originality/value: There is an increasing amount of interest in regional/local supply chains after the COVID-19 pandemic and increasing geopolitical tensions. This paper's originality is to document with an industry case study the fact that manufacturing knowledge and capabilities are the central growth engine of supply chains and that creating a new manufacturing supply chain competing with well-established clusters is not a simple matter that can be achieved through a local content policy. Such policies raise critical questions about the policy makers' implicit valuation of manufacturing technology. [ABSTRACT FROM AUTHOR]

Automated colour sorting, aided by mobile robots, is widely prevalent in the current manufacturing industry. Obstacles, such as fluctuating light conditions and camera angles, frequently hinder this procedure. Creating a colour sorting robot is a complex and time-consuming task, especially due to the vulnerability of the RGB colour space to detection errors in extreme brightness or darkness. In response to these concerns, we introduce a mobile robot that operates on the robot operating system (ROS) platform and incorporates OpenCV. This robot employs the hue, saturation, and value (HSV) colour space model for its image processing capabilities in recognising the colours and Welzl's algorithm for the ball's diameter estimation. The robot's performance was assessed across various luminous fluxes and camera tilt angles. It demonstrated exceptional performance at 64 lm and a tilt angle of 40 degrees, achieving an average accuracy of 87.5% for detecting the colour of the ball, and 81.25% for determining its location based on colour. For the ball's diameter estimation, it was found that the best estimation was received at 64 lm and 30 degrees, with both 96.32%. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore the relationship between supply chain financing (SCF) and the business risks of core enterprises, the economic value of SCF for core enterprises and the motivation for core enterprises to participate in SCF. The authors also examine the mediating effects of financing constraints. Design/methodology/approach: This study analyzes the panel data of 393 companies listed on the main board of the A-share market in China from 2011 to 2014 using fixed-effect and intermediary-effect models. Findings: The development of SCF in core enterprises can significantly reduce business risk by alleviating financing constraints. Research limitations/implications: The study sample is from China's A-share market, which may limit the ability to generalize results. The indicators used to measure SCF primarily consider commercial credit, which may have affected the accuracy of the study. Practical implications: This study provides a new basis for core enterprise managers in the manufacturing sector to conduct SCF and control business risks. SCF with small and medium-sized upstream and downstream enterprises can reduce business risks and enhance competitiveness, especially under financing constraints. Originality/value: This study focuses on core enterprises, a topic less explored in academia. It examines the impact of SCF on their performance and the mediating role of financing constraints. This study offers a novel perspective on the SCF transmission mechanism of supply chain finance and provides new insights for core enterprises. [ABSTRACT FROM AUTHOR]

In order to establish principles for implementing requirements contained in legal acts regarding methods of preventing serious industrial accidents, a study of the procedures in place at NITROERG SA, a company manufacturing explosives, was conducted. The analysis also included regulations concerning actions to be taken in the event of an accident, aimed at minimizing negative impacts on people and the environment. Legislative solutions imply the necessity for business entities to submit reports to emergency services, while also carrying out a range of activities to counteract threats associated with serious accidents. This article presents how these recommendations are implemented by the company and the methods of obtaining data to improve the undertaken projects. However, incidents in recent years indicate the need for further verification of processes to eliminate risks. [ABSTRACT FROM AUTHOR]