Parallel Production Systems Research Articles

Inverse data envelopment analysis for parallel production systems: an analysis in four types of Chinese banks

Inverse data envelopment analysis for parallel production systems: an analysis in four types of Chinese banks

Optimal maintenance policies for three-unit parallel production systems considering yields

Many production facilities consist of multiple parallel units to facilitate the completion of production plans, yet these devices are inevitably prone to malfunctions with increased operating time. Therefore, developing the optimal maintenance policy to maximize the production capacity of production facilities is a crucial issue. This paper focuses on determining the optimal maintenance policy for a three-unit production system, aiming to maximize its yield. The optimal solution is provided based on the given maintenance policy, and a general optimal maintenance policy for the system is derived. The properties related to the optimal maintenance policy are analyzed. The proposed model offers two notable contributions when compared to existing research. Firstly, a maintenance policy based on the number of visits and yields is developed. Secondly, the parallel assumption of the system and the assumption that the subsystems satisfy any distribution are in line with reality, enriching the research on maintenance strategies for production systems. To illustrate the results of the model, a numerical example is presented.

The decomposition of efficiency in parallel network production models

Kao (2012) proposed a method to decompose DMU efficiency into sub-unit efficiencies for parallel production systems. We provide a numerical example showing that the proposed method can yield negative sub-unit efficiency scores under variable returns to scale, against common sense and standard postulates requiring this score to be non-negative. As a solution, we propose a decomposition based on the directional distance function that does not suffer from this problem. In particular, we recognize that the overall inefficiency of the DMU is composed of the sub-units technical inefficiencies and a reallocation inefficiency component. The proposed method can be also applied to non-convex technologies, therefore providing a more general method to implement such a decomposition. Given the connection between the directional distance function and slack-based efficiency measurement, the method can easily be extended to this case as well.

Performance of a concurrent parallel production system through new operating curves of Six Sigma metrics

Performance of a concurrent parallel production system through new operating curves of Six Sigma metrics

Determining the optimal production–maintenance policy of a parallel production system with stochastically interacted yield and deterioration

In this paper, we study the integrated production–maintenance optimization problem of a multi-component deteriorating machine. The deterioration of each component is described by a discrete-time Markov chain with finite state space. To meet a constant demand, production planning is scheduled based on the system deterioration and the inventory level. We consider the mutual dependence between the production and the system deterioration. For each component, its deterioration transition probabilities depends on its own characteristics and its production quantity. Production yield is stochastically decreasing with the system deterioration. Maintenance is scheduled immediately if at least one component failure occurs. Otherwise, the decision-maker need to determine whether to schedule a preventive maintenance or to continue producing. We formulate the problem into a Markov decision process framework. The total discounted costs including the production costs, maintenance costs and holding/backlogging costs in the infinite horizon is obtained. Some structural properties of the optimal policy with respect to the machine condition, the inventory level are presented under mild conditions. The proposed model is further examined by a numerical example, where the properties of the production and maintenance planning and the corresponding cost are investigated. It can provide theoretical reference in managing the production and maintenance problems in multiple production lines.

Provincial energy and environmental efficiency analysis of Chinese transportation industry with the fixed-sum carbon emission constraint

Measuring energy and environmental performance has become a significant public concern, owing to increasingly severe environmental pressures. The transportation industry plays an essential role in modern economic and social development and has caused many environmental problems due to its huge energy consumption and carbon emissions. This study examined the provincial energy and environmental efficiency (EEE) of the transportation industry in China, considering a newly announced dual-carbon policy target with a total fixed-sum (FS) constraint on carbon emissions. The transportation industry is modeled as a parallel production system with passenger transportation and freight transportation. Because both subsystems would inevitably generate carbon dioxides, a parallel transportation system is innovatively considered with a FS constraint of shared carbon emissions under the dual-carbon policy target. This study contributes to the literature by measuring the EEE of the Chinese transportation industry under the FS constraint of shared carbon emissions in a parallel system. To address this problem, we propose a novel parallel data envelopment analysis (DEA) approach that considers FS shared undesirable outputs (FSSUO) based on the generalized equilibrium efficient frontier (GEEF) concept. The GEEF was obtained by minimizing the total adjustment of carbon emissions and used to calculate the overall parallel transportation efficiency. Furthermore, we developed a decomposition framework to estimate the individual passenger transportation performance and freight transportation performance. To the best of our knowledge, this is the first attempt to study the fixed-sum outputs (FSO) in a parallel production system, whereas previous studies addressed FSO in either black-box or two-stage series production systems. Finally, we apply the proposed approach to empirically analyze the EEE of the Chinese transportation industry at the provincial level from 2015 to 2019 and provide valuable empirical findings and policy suggestions.

Comparing the Performance of Serial and Parallel Production Systems through Six Sigma Metrics

Comparing the Performance of Serial and Parallel Production Systems through Six Sigma Metrics

A neutral cross-efficiency measurement for general parallel production system

There are some problems in the efficiency evaluation for parallel systems. From the applicability of existing models, the parallel models based on self-evaluation may produce the low distinguishing power and unreasonable input–output weights. From the accuracy of efficiency, the weights of partial production-units may be assigned zero values, and thereby the fail of the production-units will lead to the incomprehensibility of system efficiency. The neutral cross-efficiency model maximizes the evaluated decision-making unit (DMU) and simultaneously makes each output of the DMU being as efficient as possible, which effectively avoids the difficulty in choosing between aggressive and benevolent models, and reduces the number of zero output weights. Based on this, this paper proposes the neutral cross-efficiency evaluation method fo r general parallel systems. First, the self-evaluation models for parallel system and its production-units are developed, and the model can enable each production-unit to participate in the evaluation effectively. Then, the neutral cross-efficiency model is proposed to overcome the defects of self-evaluation model. Particularly, the proposed model is also suitable to special general parallel systems with shared resources. More importantly, the proposed models assign different input–output weights for the production-units to avoid the production-units being forced to run under identical production mechanism. Finally, two real-world examples prove the availability and effectiveness of the proposed method.

Joint optimization of production and maintenance for a serial–parallel hybrid two-stage production system

Effective machine maintenance and job scheduling strategies are two critical interactive tasks to upgrade the production efficiency in manufacturing industries. In this study, we mainly consider the interaction between production scheduling and maintenance, while optimizing the job scheduling problem in a serial–parallel hybrid two-stage production system. We formulate the problem by introducing the stochastic and workload-ratio degradation, and the actual job completion time and maintenance costs can be modeled according to the degradation status of each machine. To solve this problem, a two-step opportunistic maintenance (OM) strategy is developed, and finally an adaptive random-key genetic algorithm (GA) is designed by incorporating the OM coefficients. Numerical studies have been conducted to validate the proposed approach, and the results indicate the effectiveness compared to three existing methods under varying machine degradation scenarios.

Joint optimal maintenance strategy of accessory production system under uncertain environment

The accessory production system is the most representative system in the manufacturing industry. At present, most of the studies on the accessory production system focus on the production scheduling strategy. There is no extensive research on the maintenance strategy of accessory production system. In the real production process, the accessory production system will encounter many uncertain production factors, which will lead to system failure and affect production. Considering that the failure may originate from the external impact caused uncertainties and internal failure, the probability of failure caused by external impact is simulated by the contest success function. This paper assumes a parallel production system, and introduces the joint optimization strategy of minimum maintenance and overhaul, also balances the relationship between productivity, availability and maintenance cost, and finds the best maintenance node to improve the reliability of the production system and its actual production efficiency.

Robust optimization of uncertainty-based preventive maintenance model for scheduling series–parallel production systems (real case: disposable appliances production)

Industrial companies would attempt to keep themselves agile in the dynamic market. Given the competition among industries, lean methods are employed to reduce costs in the system. Among them, maintenance is significant to have a system available for manufacturing tasks. Maintenance is identified as the largest cost control tools in the equipment-driven industry. Implementing an effectual plan for preventive maintenance helps to be much more flexible and create an innovative solution for planning in the production. In this vein, this paper introduces an optimization model related to flexible flow-shop system scheduling in a series–parallel production system of disposable appliances by considering the preventive maintenance (PM) policy. By planning preventive maintenance, extra operation time is incurred to the system which may influence the cycle time and lead to lost sales and back orders. Therefore, the paper proposes a mathematical model to consider both operations times and availability of the whole production system to minimize the delays to reach an optimal sequence of processing. Since uncertainty exists in real industrial systems, the processing times are uncertain here. To handle uncertainty, robust optimization has been applied to solve the problem. In addition, a scenario-based genetic algorithm (SBGA) and Particle Swarm Optimization (PSO) algorithm have been developed to solve the proposed model. The results indicate the appropriate performance of the proposed approach in terms of time-saving leads to saving the cost of PM.

A column generation-based exact solution method for seru scheduling problems

This paper attempts to address production scheduling problems in seru production systems (SPS), which is a new-type manufacturing system emanating from Japanese electronic assembly industry. As a typical parallel production system, SPS has high efficiency, good flexibility, and rapid responsiveness, which are achieved by reconfiguring serus, increasing, or decreasing workers to adjust the output in practical volatile markets. The seru scheduling problem in this paper is formulated as an integer programming (IP) model to minimize the total weighted completion time (TWCT). Then, by employing the Dantzig-Wolfe decomposition, the proposed IP model is reformulated into a set partitioning problem with a master problem and several subproblems. A branch-and-bound (B&B) algorithm is designed, and each node in a B&B tree is a linear relaxation problem (LRP) of the set partitioning problem. The LRP is solved by a column generation approach, in which each column is generated to represent a schedule of the seru in SPS based on solving the subproblems. Computational experiments are conducted, and the results indicate that the proposed column generation-based exact solution method is promising in solving the seru scheduling problem effectively.

Dominance and ranking interval in DEA parallel production systems

Dominance and ranking interval in DEA parallel production systems

From peaks to ports: Insights into tin provenance, production, and distribution from adapted applications of lead isotopic analysis of the Uluburun tin ingots

Lead isotope analysis (LIA) can be applied to tin provenance studies when both the U–Th–Pb characteristics of cassiterite and potential Pb contamination are taken into account. As cassiterite (SnO2) contains higher concentrations of U than Pb and negligible Th, radioactive decay increases 206Pb/204Pb and 207Pb/204Pb ratios in cassiterite over time. However, 208Pb/204Pb ratio retains its primary value and can be correlated with LIA databases. A majority of documented Bronze Age tin ingots from Europe have Pb in excess of the 5 ppm maximum that can be derived from Cenozoic to Late Paleozoic cassiterite. A minute mass of galena (PbS) in the ore concentrate is sufficient to mask the cassiterite-derived lead, as would the addition of any lead contaminant introduced in the smelting/casting process. If the galena is cogenetic with the cassiterite, then LIA will be unaffected. The inclusion of uranium-rich minerals in the tin ore concentrate is another potential source of excess lead. In this case, the additional Pb is uranogenic, and so 206Pb/204Pb and 207Pb/204Pb will reflect the age of the uranium minerals, but 208Pb/204Pb will retain its primary value. If the U-minerals are cogenetic or coeval with tin mineralization, then a Pb isochron age will indicate the age of the ore.Between 1984 and 1994, at least 117 ingots, or roughly one tonne, of tin was raised from the Late Bronze Age Uluburun shipwreck (ca. 1320 B.C.). Over half of the analyzed ingots from this wreck site have high Pb concentrations (>100 ppm), indicative of contamination from non-radiogenic lead associated with lead metal or galena. LIA indicates that the Pb originated from the Pb–Ag-rich Bolkardağ region of the south-central Taurus Mountains. A second group of approximately 28 tin ingots with lower Pb content (<100 ppm) contain additional uranogenic Pb but retain 208Pb/204Pb compositions that overlap with the ca. 300 Ma tin regions of Western Europe and Central Asia, with the most likely source being the Tienshan Mountains in Kyrgyzstan, Tajikistan, and Uzbekistan.By compensating for previous uncertainty around the use of Pb isotopes for sourcing tin objects, it is now possible to contextualize the Uluburun tin ingots more securely within the metallurgical systems of the Central Taurus-Cilicia-Amanus axis. Recent scholarship has shown that tin production in the South-Central Taurus region had taken place at a scale not previously anticipated. Two parallel production systems appear to have been in place serving elite and common consumption networks via markedly different technologies. The South-Central Taurus and Cilician cities served as important components of maritime and terrestrial metal distribution around the eastern Mediterranean, providing a range of metals from a single geographical region.

Joint optimisation on maintenance policy and resources for multi-unit parallel production system

Multi-unit parallel production systems (MuPPSs) widely exist in many industry areas. A general requirement for the MuPPS is that each production system should continuously run and its downtime should be as short as feasible. For such systems, optimising preventive maintenance (PM) policy is crucial so that resources such as the number of spare units and that of repairmen can be optimally used. On this basis, this paper develops an optimal model jointly optimising the PM policy and the number of repairmen and spare units, for which the genetic algorithm is used to determine the optimal displacement sequence of spare units. According to the developed model, a real case study of a train working line is presented to demonstrate its necessity. Finally, the sensitivity analysis is conducted to assess the influence of some parameters on the optimal results.

Separable models for interconnected production-inventory systems

We investigate a new class of separable systems which exhibit a product-form stationary distribution. These systems consist of parallel production systems (servers) at several locations, each with a local inventory under base stock policy, connected with a common supplier network. Demand of customers arrives at each production system according to a Poisson process and is lost if the local inventory is depleted (“lost sales”). To satisfy a customer’s demand a production server needs raw material from the associated local inventory. The supplier network is a classical queueing network. We investigate two different lost sales regimes, either based on total inventory or on available inventory. We perform cost analysis to find the optimal base stock levels, which is due to the product-form stationary distribution a separable optimization problem. Finally, we demonstrate that the explicit product forms for both stationary distributions enable us to compare main performance metrics of the systems under the different lost sales admission regimes.

Quasi-Periodic Replacement Policy for a Two-Unit Production System

Maintenance optimization of periodic replacement for mono-unit production system is a widely discussed topic. In practice, the replacement for a parallel production system with multi-unit served by one repairman is universal. The replacement action is often implemented in a maintenance window at random, although the replacement period appears as a quasi-periodic event. To optimize these maintenance policies, this study analyzes a bivariate quasi-periodic replacement policy (T, W) for a two-unit parallel production system with a maintenance window and one repairman. One unit of the system is replaced when either a failure occurs or a replacement plan comes in the maintenance window, whichever comes first. If one of the two units is in the replacement, the other may continue operating or waiting until the replacement is completed. An optimal replacement window [T*, T* + W*] can be obtained by jointly considering the system’s long-running cost rate and the availability using the genetic algorithm. This study also introduces three examples of the production system with different types of units to illustrate the proposed policy.

Horizontal integration management: An optimal switching model for parallel production system with multiple periods in smart supply chain environment

Horizontal integration via a new generation of global value chain network is a main characteristic of Industry 4.0. As a contribution to the achievement of smart supply chain, optimal operation management for horizontal integration of production network has been paid attention to recently. This paper aims to derive an optimal switch model considering production, due date and quality for parallel production system with multiple periods in smart supply environment. Due to the customer needs of cost and delivery date shorting, prompt change in the production plan became more important. In the multi period system (For instance, production line.) where target processing time exists, production, idle and delay risks occur repeatedly for multiple periods. In such situations, delay of one period may influence the delivery date of an entire process. This kind of problem is called “a limited-cycle problem with multiple periods”, and is seen in production lines, time-bucket balancing, and production seat systems and so on. In this paper, we discuss minimum expected cost including production, due date and quality in a parallel production process, where the risk depends on the previous situation and occurs repeatedly throughout multiple periods. Also, the policy of optimal switching for parallel production system will be analysed. The results of numeric experiment in this paper show that the proposed optimal switching model can contribute to the scientific knowledge on the development of integrated solutions for parallel production system.

A Condition-Based Maintenance Policy (CBM) of Repairable Multi-Component Deteriorating Systems Based on Quality Information

The maintenance decision analysis of equipment has always been one of the hot spots of concern for researchers. A maintenance policy for parallel production systems is investigated in this study, with the parallel components having equal cost parameters. The rejection rate indicates the degradation degree of the machine, and the rejection rate is assumed to be obtained by detection. The maintenance strategy proposed in this paper involves two threshold values. By optimizing with genetic algorithm, the threshold values [Formula: see text] and [Formula: see text] corresponding to the minimum expected total cost can be found. Finally, the result of sensitivity analysis is shown that the cost parameter has a great influence on the threshold values.

System efficiency evaluation of homogeneous parallel production systems: An aggregation approach

Existing models, for efficiency evaluation of DMUs with homogeneous parallel production-units, have limitations in the sense that production process of a DMU is compared with the production possibility set of all production-units. Moreover, same set of input-output weights is used to evaluate the efficiency, project inputs-outputs of a DMU and all its production-units. This means, all the production-units of a DMU operate in a similar way in the long run as if they are not separate production-units but one single entity. We propose an aggregation approach to evaluate the efficiency of DMUs with homogeneous parallel production-units. We also introduce Weighted Average Efficiency and System Efficiency. As opposed to the existing methodology, different set of weights are used to evaluate efficiency of different production-units of a DMU. Finally, the proposed methodology has been used to evaluate the efficiency of higher education sector of Bihar, one of the largest states in India.