This paper develops an integrated economic model for the joint optimization of quality control parameters and a preventive maintenance policy using the cumulative sum (CUSUM) control chart and ...variable sampling interval fixed time sampling policy. To determine the in-control and out-of-control cost for both mean and variance, a Taguchi quadratic loss function and modified linear loss function are used, respectively. Imperfect preventive maintenance and minimal corrective maintenance policies were considered in developing the model, which determines the optimal values for significant process parameters to minimize the total expected cost per unit of time. A numerical example is used to test the model, which is followed by a sensitivity analysis. The integration of CUSUM mean and variance charts with the maintenance actions are proven successful to detect the slightest shift of the process. The findings reveal that among all the cost components, process failure due to external causes and equipment breakdown has a noteworthy attribute to the total costs of the optimized model. It is expected that top managers can utilize the suggested combined model to minimize the costs related to quality loss and maintenance policy and achieve economical advantages as well.
This study develops a mathematical model to mitigate disruptions in a three-stage (i.e., supplier, manufacturer, retailer) supply chain network subject to a natural disaster like COVID-19 pandemic. ...This optimization model aims to manage supply chain disruptions for a pandemic situation where disruptions can occur to both the supplier and the retailer. This study proposes an inventory policy using the renewal reward theory for maximizing profit for the manufacturer under study. Tested using two heuristics algorithms, namely the genetic algorithm (GA) and pattern search (PS), the proposed inventory-based disruption risk mitigation model provides the manufacturer with an optimum decision to maximize profits in a production cycle. A sensitivity analysis was offered to ensure the applicability of the model in practical settings. Results reveal that the PS algorithm performed better for such model than a heuristic method like GA. The ordering quantity and reordering point were also lower in PS than GA. Overall, it was evident that PS is more suited for this problem. Supply chain managers need to employ appropriate inventory policies to deal with several uncertain conditions, for example, uncertainties arising due to the COVID-19 pandemic. This model can help managers establish and redesign an inventory policy to maximize the profit by considering probable disruptions in the supply chain network.
Analytic Hierarchy Process (AHP) model was applied to select the most appropriate package of Solar Home System (SHS) for rural electrification in Bangladesh. Three different packages (75 Wp, 50 Wp ...and 30 Wp) were considered for selection and expert's opinions based on three attributes: i) cost, ii) meeting the electricity demand of basic household need and iii) availability of package in local market were taken to quantify relative priorities. After an intensive analysis through AHP model, it was found that 30 Wp system was the most appropriate package (percentage of priority was 42.19%) of SHS for rural electrification in Bangladesh. The useable items of this package are 2 lamps; each 8 Watt capacity and a black and white television. Customers can get it with cash price of BDT 12500 (US$ 162.34), although, different credit and pricing options are also available. 30 Wp SHS is also financially feasible for suppliers with Internal Rate of Return (IRR) value as 28%.
► This paper highlights the application Analytic Hierarchy Process model. ► Three alternative packages of SHS were considered for selection. ► The selection was based on three important criteria. ► 30 Wp system was the most appropriate package of SHS in Bangladesh.
The disruption has a significant impact on supply chain collaboration (SCC) which is an important task to improve performance for many enterprises. This is especially critical for small- and ...medium-sized enterprises (SMEs). We developed a decision-modeling framework for analyzing SCC barriers in SMEs for the emerging economy in Bangladesh. Through literature review and expert opinion survey, we have identified a comprehensive list of SCC barriers under four main categories, namely, information-related, communication-related, intra-organizational, and inter-organizational barriers. Then we applied the Grey DEMATEL and Fuzzy Best-Worst methods to evaluate these SCC barriers and compared the results. We also conducted a sensitivity analysis to assess the robustness of the proposed approach. The study reveals that lack of communication is the most crucial barrier in SCC, providing a model for assessing barriers in other emerging economies. This study contributes to the literature by analyzing SCC barriers and by comparing the results obtained from two different MCDM methods. The findings of this study can help decision-makers to plan for overcoming the most prioritized SCC barriers which ultimately contribute to improving the resilience and sustainability performances of SMEs.
This study develops an inventory model to solve the problems of supply uncertainty in response to demand which follows a Poisson distribution. A positive aspect of this model is the consideration of ...random inventory, delivery capacities and supplier’s reliability. Additionally, we assume supplier capacity follows an exponential distribution. This inventory model addresses the problem of a manufacturer having an imperfect production system with single supplier and single retailer and considers the quantity of product (Q), reorder points (r) and reliability factors (n) as the decision variables. The main contribution of our study is that we consider supplier may not be able to deliver the exact amount all the time a manufacturer needed. We also consider that the demand and the time interval between successive availability and unavailability of supplier and retailer follows a probability distribution. We use a genetic algorithm to find the optimal solution and compare the results with those obtained from simulated annealing algorithm. Findings reveal the optimal value of the decision variables to maximize the average profit in each cycle. Moreover, a sensitivity analysis was carried out to increase the understanding of the developed model. The methodology used in this study will help manufacturers to have a better understanding of the situation through the joint consideration of disruption of both the supplier and retailer integrated with random capacity and reliability.
Abstract
With increasing awareness about society and the environment, industries are urged to develop and implement sustainable supply chain (SSC) processes. However, the risk of non‐compliance ...against these SSC processes to manage overall business risks, namely, avoiding reputational damage and managing financial losses, is increasingly receiving senior management attention. Given these shortcomings, the objective of this research is twofold, namely, (i) to identify and evaluate barriers adopting sustainable supply chain risk management (SSCRM) processes and (ii) to prioritize SSCRM strategies to overcome these barriers in an emerging economy, namely, Bangladesh. To achieve the objectives, this study develops a framework by integrating the
technique for order of preference by similarity to ideal solution
(TOPSIS) and
VIsekriterijumska optimizacija i KOmpromisno Resenje
(VIKOR). The results show that the “information‐related barriers” are most prevalent among the categories of barriers, and “lack of coordination and collaboration” has been identified as the most significant barrier. Evaluating the strategies, “top management commitment” is the best strategy. These findings can help managers develop strategies to overcome the most significant barriers to adopting SSCRM. The proposed framework, which integrates quantitative and qualitative approaches, can be used by decision‐makers to make accurate, prompt, and systematic decisions compliant with SSCRM business processes.
•A joint facility location and inventory model is developed.•Partial-disruption risk is considered.•A modified particle swarm optimization is proposed to solve the model.•The impact of the customer's ...decision to accept or reject backorder has analyzed.•The use of substitute products as a risk management strategy has analyzed.
This paper studies a joint facility location and inventory model from the viewpoint of partial-disruption risk—i.e., when manufacturing facilities meet the demands of third-party distribution centers with a portion of their capacity, free from any disruptions—while considering substitute products as a disruption risk mitigation strategy. We considered these third-party distribution centers as the customers of the manufacturing facilities. We used a multinomial logit model to rank-order the facilities according to customers’ preferences. Then, a non-linear integer programming model was developed which attempted to assign a sequence of facilities to each customer based on their preferences while at the same time, minimizing the total supply-chain cost. We also considered customers’ decisions for backorders while developing the model. Due to the NP-hard nature of the problem, we developed a particle swarm optimization-based metaheuristic algorithm to solve the model. The efficiency of the modified particle swarm optimization (MPSO) was illustrated through computational tests and systematic comparison with the exact method, a hybrid meta-heuristic algorithm including tabu search (TS) and variable neighborhood search (VNS) from the literature, and its modified form (Modified TS-VNS). A numerical example was used to show the applicability of the model. Finally, we gained useful insight into the role of substitute products and customers’ decisions for backorders through scenario-based analysis. We found that the total supply chain cost could increase in disruption scenarios when customers were more likely to refuse backorder offers. However, the cost-saving from producing a substitute for key products could be significant.
PDF
