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The competitiveness of the companies depends on continuous progress, and the allocation of the continuous improvement is crucial in today’s market competition. The main approaches proposed in the literature are distributed and centralized policies. This research proposes a novel model for resource allocation that surpasses existing methods. It leverages throughput rate evaluation as the core principle. This model considers key improvement parameters and utilizes a mathematical framework to allocate improvement resources to each parameter. The experiments conducted concern failure parameters (Mean Time Between Failures and Mean Time To Repair), setup time, defective rate, bottleneck numbers and the increasing processing time of the bottleneck. The original contribution is twofold: the evaluation considers a wider range of conditions and their impact on flow line’s sustainability. The model emphasizes sustainability by focusing on minimizing the idle time of workstations within the flow line. Numerical analysis of the proposed model reveals a substantial reduction in total idle time improving the related energy consumption. Furthermore, the model achieves a throughput rate that closely aligns with the centralized policy, traditionally considered the most effective approach.

The competition and the volatility of today’s production context require that enterprises are able to rapidly adapt to changes, reducing total costs in production. The main relationship between producer and consumer can be conducted through Make-To-Order (MTO) or Make-To-Stock (MTS) systems. This study proposes a hybrid MTS and MTO production system with a dynamic decoupling point. The proposed model concerns the monitoring of earliness and tardiness of customer orders to move the decoupling point towards MTS or MTO. Simulation models are proposed to test the proposed model following periodic or continuous review. The numerical results highlight that the best dynamic approach is the periodic review, which is more effective when the customer demand rate is higher.

Throughout much of the 20th century, Sn–Pb solder dominated electronics. However, environmental and health concerns have driven the adoption of lead-free alternatives. Since 2006, legislation such as the European Union’s RoHS Directive has mandated lead-free solder in most electronic devices, prompting extensive research into high-performance substitutes. Lead-free solders offer advantages such as reduced environmental impact and improved reliability but replacing Sn–Pb presents challenges in areas like melting point and wetting ability. This transition is primarily motivated by a focus on protecting environmental and human health, while ensuring equal or even improved reliability. Research has explored lead-free solder’s mechanical properties, microstructure, wettability, and reliability. However, there is a notable lack of studies on its long-term performance and lifetime influence. To address this gap, mathematical models are used to predict intermetallic bond evolution from process conditions, validated with experimental tests. This study contributes by extending these models to predict bond evolution under typical operating conditions of devices and comparing the predictions with actual intermetallic thickness values found through metallographic sections.

The study and advancement of crank-slide actuating mechanisms based on four-link structural groups are promising for the development of new designs of crank presses and other stamping and forging machines [...]

Cyber-physical systems, cloud computing, the Internet of Things, and big data play significant roles in shaping digital and automated landscape manufacturing. However, to fully realize the potential of these technologies and achieve tangible benefits, such as reduced manufacturing lead times, improved product quality, and enhanced organizational performance, new decision support models need development. Game theory offers a promising approach to address multi-objective problems and streamline decision-making processes, thereby reducing computational time. This paper aims to provide a comprehensive and up-to-date systematic review of the literature on the application of game theory models in various areas of digital manufacturing, including production and capacity planning, scheduling, sustainable production systems, and cloud manufacturing. This review identifies key research themes that have been explored and examines the main research gaps that exist within these domains. Furthermore, this paper outlines potential future research directions to inspire both researchers and practitioners to further explore and develop game theory models that can effectively support the digital transformation of manufacturing systems.

Reconfigurable manufacturing systems (RMSs) are extensively studied and employed to address demand uncertainties. RMS machines are designed to be modular and adaptable to changing requirements. A recent innovation is the introduction of multi-spindle reconfigurable machines (MRMTs). This study evaluates the impact of MRMTs’ introduction into an RMS, considering factors such as the number of MRMT machines and reconfiguration policies. A simulation model incorporating failures, process time variability, and part inter-arrival supports the analysis. The numerical results aid decision makers in determining the optimal RMS configuration with MRMTs. The simulation outcomes indicate that a balanced number of multi-spindle machines can significantly enhance performance compared with an unbalanced distribution.

Workload Control is used in manufacturing systems to obtain more predictable throughput times and accurate delivery dates. The models proposed in the literature are typically focused on machines with fixed processing time. This study, therefore, uses simulation to investigate the performance of the Workload Control method with a controllable processing time of the machines. This research proposes four models to support the decisions on the time to reconfigure the machines and the number of machines reconfigured. The time decision follows two strategies as periodic and continuous, while the machines reconfigured can be all or two considering the workload. The combinations of these strategies lead to four models that are tested in different conditions of reconfiguration times and the number of bottlenecks. The results suggest as the proposed models allow to improve delivery time performance and a more uniform distribution of workload among the machines of the manufacturing systems.

The reduction in emissions and the increase in energy costs push companies to identify solutions to reduce energy consumption in production systems. One of the approaches proposed in the literature is the shutdown of machines to reduce energy consumption in the idle state. This solution does not affect production processes and can be applied in various manufacturing fields. This paper proposes switch-off policies in manufacturing systems under a workload control system. The shutdown policies developed consider the number of items in the queue and the calculation derived from the workload control mechanism. Simulation models have been developed to test the proposed policies using the case always on as a benchmark, considering different levels of absorbed power in the inactivity and warm-up states and different warm-up times. The results highlight how the switch policies that include the workload evaluation drastically reduce the number of on/off activities, assuring lower energy consumption.

In recent years, assembly line design methodologies have included the possibility of sharing tasks between stations. These approaches increase the throughput, improving the workload balance among the stations. Sharing operations can support the management of assembly lines with task redundancy. The redundancy of the tasks between two consecutive stations improves the robustness of the assembly line to unforeseen events. A control policy that allocates the shared tasks between two adjacent stations is crucial for the performance of the assembly line. This paper proposes a fuzzy approach to distributing the workload of the shared tasks between two consecutive stations. The fuzzy model allows for the distribution of the workload between the stations in a more gradual way. Simulations were conducted to allow for a performance evaluation with a model proposed in the literature. The results show how the fuzzy model improves all the performance measures evaluated; in particular, when the inter-arrival of the raw items is rather stable. In these conditions, the reduction of the average time and its standard deviation is about 50% to 80%, while the reduction of the work in process is about 60% to 90%. These benefits are obtained with a relevant increase of the variations of the average utilization of the stations.

Cellular manufacturing systems are widely used due to their advantageous capability of combining the flexibility of the job-shop and the productivity of the flow-shop. In recent years, the reduction of the product life cycle, variation in demand products, and introduction of new technologies, have driven the manufacturing companies to improve responsiveness, thus reducing the cellular manufacturing life cycle with a focus on re-designing the cells. Another issue concerns the sustainability of the manufacturing systems due to the introduction of energy costs in the design model of cellular manufacturing systems. This study is an overview of the more recent works on design approaches to improve the responsiveness and the models to support the sustainability of cellular manufacturing systems. The analysis of the literature review highlights the main findings and suggests future development paths considering the open problems in this field.

The “Fourth Industrial Revolution” (alternatively known as “Industry 4 [...]

Most job shops in practice are constrained by both machine and labor availability. Worker assignment in these so-called Dual Resource Constrained (DRC) job shops is typically solved in the literature via the use of meta-heuristics, i.e. “when” and “where” rules, or heuristic assignment rules. While the former does not necessarily lead to optimal results, the latter suffers from high computational time and complexity, especially when there is a large number of workstations. This paper uses game theory to propose a new worker assignment rule for DRC job shops. The Gale-Shapley model (also known as the stable marriage problem) forms a ‘couple’ made up of a worker and machine following a periodic review strategy. Simulation is used to evaluate and compare the proposed model to “when” and “where” rules previously proposed in the literature. Simulation experiments under different conditions demonstrate that the Gale-Shapley model provides better results for worker assignments in complex DRC systems, particularly when the workers have different efficiency levels. The implications of the findings for research and practice are outlined.

The processing time of the machine is assumed fixed in several studies. In many real industrial applications, the processing time is affected by learning and forgetting effects. This research proposes a scheduling approach to support a manufacturing system under learning/forgetting effect. The approach is supported by a Multi-Agent System to perform the scheduling activities in a quasi-real-time and in general manufacturing systems. A simulation environment is developed to test the proposed approach and the results are compared with a benchmark model for evaluating several performance measures of the manufacturing system. The simulation results highlight how the proposed approach improves all the performance measures under different conditions of inter-arrival time, learning and forgetting rates. A complete Analysis of the Variance highlights the main effects on the performance measures to support the decision maker of the manufacturing system.

The energy storage system is typically used in manufacturing systems with renewables to reduce the impact of the instabilities of these sources. The switch-off policies are proposed in the literature to reduce the energy used by the machines in the idle state. This study uses simulation models to investigate the potential application of the energy storage system with switch-off policies to reduce the energy costs related to the use over the peak power constraint. The manufacturing system analyzed is a flow line with the possibility of introducing two switch-off policies considering the two parameters of the battery (capacity and charge rate) and three levels of power fluctuations needed by the manufacturing operations. The results highlight that the charge rate and the power fluctuations of the manufacturing operations are the more important factors that impact the model studied. The switch-off policies have a positive impact and can reduce the energy use over the peak power constraint even at a slower charge rate, which means battery at a lower cost.

Abstract The buffer allocation problem is an NP-hard combinatorial optimization problem, and it is an important design problem in manufacturing systems. The research proposed in this paper concerns a product line consisting of n unreliable machines with n − 1 buffers and a preventive maintenance policy. The focus of the research is to obtain a better trade-off between the buffer level and the preventive maintenance actions. This paper proposes a dynamic control of the buffers’ level and the interval between two consecutive preventive actions. The set of the parameter of the proposed policy allows choosing the reduction in the costs or the increment of the throughput rate. A simulation model is developed to test the proposed model to the solution proposed in the literature. The proposed policy leads to better results in terms of total costs reduction keeping high production rate, while the design of a fixed level of buffer works better for lower production rates required.

Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

The research discusses in this paper concerns the improvement allocation policies to reduce the process time in job-shop manufacturing systems. The policies proposed are based on the evaluation of the workload control of the entire manufacturing system. Three policies are proposed: centralized, distributed and proportional. A simulation model is used to test the proposed policies under different conditions as: static and dynamic demand; introduction of machine breakdowns; different level of average manufacturing system utilization. The performance measures are compared to a manufacturing system without policies. The simulation results show that the improvement allocation allows to improve the performance with limited investment (average reduction of process time needed) and how the machine breakdowns and demand changes lead to different better policy. The decision maker can use these results to decide the better policy to use.

Manufacturing systems need to be able to work under the dynamic and uncertain production environment. Machine and routing flexibility combined with preventive maintenance actions can improve the performance of the manufacturing systems under dynamic conditions. This paper evaluates different levels of machine and routing flexibility combined with different degrees of preventive maintenance policy. The performance measures considered are throughput, work in process and throughput. The performance measures are compared with a system without any flexibility and no preventive maintenance actions. Different levels of flexibility and preventive maintenance actions are examined under a simulation environment. The simulation results highlight more important factors for the performance measures and the best combination of the factors to improve the performance.

The classical models for designing production lines follow the objective of balancing the line so as to improve the throughput [...]

Workload control mechanisms are widely studied in the literature for the control of job-shop systems. The control of these systems involves acceptance, order release and priority dispatching. At the release level, the workload norm controls the “enters” of the jobs; it is relevant how the aggregate workload is computed. Few works have studied new computation methods of the aggregate workload but use the adjusted aggregate workload proposed in the literature. This paper proposes a dynamically adjusted aggregate workload to improve the performance of the workload control mechanism in job-shop systems. The adjusted aggregate workload is updated when each part exits from a workstation; this means that the workload used to release the orders is related to the state of the job shop in real-time. Simulation is used to evaluate and compare the proposed model to the classical models proposed in the literature. The simulation experiments demonstrate improvement of performance and how the model proposed is robust under different manufacturing system conditions.

The peak power of the manufacturing systems can increase electricity costs and reduce the use of renewable energy suppliers. The power of the machining processes depends on the processing time of the operations. Then, the allocation of the power to the machines of a manufacturing system controls the processing time of the manufacturing operations. An efficient allocation model can reduce the peak power, keeping the throughput performance level. This paper proposes a game theory to allocate the power to the machines including the dependence of the processing time from the power allocated. The game model uses the Gale-Shapley algorithm that forms couples of under and overloaded machines. Then, each couple exchanges the power from the underloaded to overloaded machines. The model considers the global workload and the jobs in queue for each machine. A simulation model tests the proposed method compared to a benchmark where each machine works with fixed power. The simulation results show how the model can improve the performance of the manufacturing system in several conditions tested. In particular, the main benefits can be obtained when the manufacturing system has high or medium utilization or the uncertainty affects the processing time.

One of the most promising approaches to reduce the amount of energy consumed in manufacturing systems is the switch off policy. This policy reduces the energy consumed when the machines are in the idle state. The main weakness of this policy is the reduction in the production rate of the manufacturing systems. The works proposed in the literature do not consider the design of the production lines for the introduction of switch off policies. This work proposes a design model for production lines that include a targeted imbalance among the workstations to cause designed idle time. The switch-off policy introduced in such designed production lines allows for a reduction in the energy consumed with any production rate loss. Simulation tests are conducted to verify the benefits of switch off policies in production lines designed for its. The simulation results show that the proposed line design allows for a reduction in energy consumption, with a defined loss in the throughput. The application of switch-off policies in the proposed flow line leads to a significant reduction in the energy used in unproductive states controlling the production loss.