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DR. BIKASH KOLI DEY is a post-doctoral researcher in the Department of Industrial Engineering, Hongik University, South Korea. He has completed his B.Sc. with Mathematics as a Major in 2012 and M.Sc. in 2014 in Applied Mathematics from Vidyasagar University, India. He obtained his Ph.D. from Banasthali Vidyapith, India in 2019 in the field of Operations Research (Applied Mathematics). He has published 13 journal articles in reputed journals of Applied Mathematics and Industrial Engineering. His citations increase by more than 200. He is a member of several reputed learned societies. He is reviewer of several national and international journals. He is also guest editor of one International journal.
The concept of controllable lead time and variance is critical issues for the smart supply chain management. This study concerns about variable lead time and variance under controllable production rate and advertise-dependent demand. Managers of any supply chain always improve their performance by reducing lead time and its variance. This paper explores and quantifies these benefits of such lead time reduction for commonly used lot size quantity, production rate, safety factor, reorder point, advertisement cost, vendor’s setup cost. Instead of expected total cost equations, this study provides an exact total cost equation built on an inherent relationship between on-hand inventory and backorder. The marginal value analysis on lead time and its variance achieve more accurate results. The analytical results show that the total supply chain cost is a convex function of both lead time and variance. In other words, the cost savings on both lead time and its variance reduction decrease when lead time becomes larger. Two continuous investments are implied to reduce setup costs and improve the reliability of the production process. The expected backorder and inventory for the buyer uniformly distributed throughout reorder point. Moreover, a smart production process is developed under stochastic demand and flexible production rates. The global optimality of the cost function and decision variables are validated through classical optimization. The numerical examples confirm analytical results and sensitivity analysis is provided for different parameters. Some special cases along with graphical representations are given to validate the model.
Bikash Koli Dey; Shaktipada Bhuniya; Biswajit Sarkar. Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Expert Systems with Applications 2021, 184, 115464 .
AMA StyleBikash Koli Dey, Shaktipada Bhuniya, Biswajit Sarkar. Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Expert Systems with Applications. 2021; 184 ():115464.
Chicago/Turabian StyleBikash Koli Dey; Shaktipada Bhuniya; Biswajit Sarkar. 2021. "Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management." Expert Systems with Applications 184, no. : 115464.
Every industry always tries to provide the best service to its consumers. To provide better service to the consumer and optimize profit, a sustainable online-to-offline retailing strategy is proposed in this current study. Both online and offline systems are considered here, i.e., to provide the best service, the industry sells its products online and offline. Due to the consideration of online and offline systems, the selling price of the products is also different for different modes, and the demand for a particular product is the combined demand of online demand and offline demand, which depend on the selling price of the product. Moreover, the exact lead time and exact backorder are calculated to obtain the system’s exact cost or profit, which directly improves the system’s service. Different investments are incorporated to optimize the total system profit. A distribution-free approach is utilized to solve this model. Numerical examples are provided to prove the applicability of the model in reality. Sensitivity analysis is performed based on critical parameters. Special cases and graphical representations also prove the global optimality of the current study.
Biswajit Sarkar; Bikash Dey; Mitali Sarkar; Ali AlArjani. A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand. Sustainability 2021, 13, 1756 .
AMA StyleBiswajit Sarkar, Bikash Dey, Mitali Sarkar, Ali AlArjani. A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand. Sustainability. 2021; 13 (4):1756.
Chicago/Turabian StyleBiswajit Sarkar; Bikash Dey; Mitali Sarkar; Ali AlArjani. 2021. "A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand." Sustainability 13, no. 4: 1756.
The concept of advanced sustainable inventory management, where demand pattern stock level and advertising dependent under trade-credit policy is taking account in this present study. Optimal credit period and cycle time are the main objective of this advanced system. A developed solution methodology is derived to show the existence of global optimality under optimum credit period and cycle time. The main concern of this advanced system is to maximize the annual total system profit of retailer with finite replenishment rate. Numerical illustration are carry forward for different cases to prove the stainability along with real impact of this model. Sensitive analysis for the key parameters is discussed in sensitivity analysis section along with some real managerial insights.
Buddhadev Mandal; Bikash Koli Dey; Sudhansu Khanra; Biswajit Sarkar. Advance sustainable inventory management through advertisement and trade-credit policy. RAIRO - Operations Research 2021, 55, 261 -284.
AMA StyleBuddhadev Mandal, Bikash Koli Dey, Sudhansu Khanra, Biswajit Sarkar. Advance sustainable inventory management through advertisement and trade-credit policy. RAIRO - Operations Research. 2021; 55 (1):261-284.
Chicago/Turabian StyleBuddhadev Mandal; Bikash Koli Dey; Sudhansu Khanra; Biswajit Sarkar. 2021. "Advance sustainable inventory management through advertisement and trade-credit policy." RAIRO - Operations Research 55, no. 1: 261-284.
The proposed model focuses on an imperfect production process (IPP) in which, during long-term production, the system may change to an “out-of-control” state from an “in-control” state and produce some imperfect products because of a long production run length. Brand image and industry reputation are affected by product defectiveness. To increase the profit of any industry and improve reputation and brand image, inspection of the production system is required. However, this inspection is subjected to human error, which negatively affects the assessment of production systems. Herein, an error-free inspection is performed with the help of an autonomation policy, in which each product is inspected via a machine instead of a human, facilitating an error-free inspection and converting the production system to a smart production system. Moreover, in reality, product demand cannot always be constant. Therefore, in this model, a selling-price-dependent demand is considered along with a variable production rate to enhance model applicability. Moreover, total system profit is optimized and optimal values for production run time, inspection scheduling, selling price, buffer inventory, and production rate are determined. Finally, for model validation, some numerical examples along with special cases are provided. The concavity of the optimal function is also proven through graphical illustration. The sensitivity of the key parameters of the presented model is explored and the significance is explained.
Bimal Kumar Sett; Bikash Koli Dey; Biswajit Sarkar. Autonomated Inspection Policy for Smart Factory—An Improved Approach. Mathematics 2020, 8, 1815 .
AMA StyleBimal Kumar Sett, Bikash Koli Dey, Biswajit Sarkar. Autonomated Inspection Policy for Smart Factory—An Improved Approach. Mathematics. 2020; 8 (10):1815.
Chicago/Turabian StyleBimal Kumar Sett; Bikash Koli Dey; Biswajit Sarkar. 2020. "Autonomated Inspection Policy for Smart Factory—An Improved Approach." Mathematics 8, no. 10: 1815.
The present study focuses on a single-vendor, single-buyer supply chain model for a single type of product with upgraded service provided to the buyer by the vendor. Vendors often increase their profit by providing a lower quality of a particular product. In this study, an advanced supply chain model is developed to increase service in the presence of an unreliable vendor and an online-to-offline (O2O) channeling system. The vendor provides lower quality items to the customer, even though they had committed to providing a certain quality product, in order to increase their profit. For more realistic results, demand is considered to be price-, quality-, and service-dependent. To advertise and sell the products, the manufacturer uses an online system, which the buyer also uses to choose and order the product, where the particular product is delivered to the customer by a third (offline) party; that is, the concept of an O2O retail channel is adopted to improve the service level of the supply chain management (SCM). To control the out-of-control state and improve the production quality, investment is used. Contrary to the literature, service is considered to be constrained, which makes the model more realistic. A classical optimization technique is used to solve the model analytically and a two-echelon supply chain model is obtained under the advanced O2O retail channel, along with optimized profit, shipment volume, selling price, ordering cost, service, back-ordered price discount, lead time, and safety factor values. Some numerical examples and a sensitivity analysis of the key parameters are provided, along with graphical representation, in order to validate the model.
Bimal Kumar Sett; Bikash Koli Dey; Biswajit Sarkar. The Effect of O2O Retail Service Quality in Supply Chain Management. Mathematics 2020, 8, 1743 .
AMA StyleBimal Kumar Sett, Bikash Koli Dey, Biswajit Sarkar. The Effect of O2O Retail Service Quality in Supply Chain Management. Mathematics. 2020; 8 (10):1743.
Chicago/Turabian StyleBimal Kumar Sett; Bikash Koli Dey; Biswajit Sarkar. 2020. "The Effect of O2O Retail Service Quality in Supply Chain Management." Mathematics 8, no. 10: 1743.
This paper investigates an impact of random defective rates in an imperfect production system with multiple products and planned backorders in a single-stage production system. The purpose of this study is to control a single-stage cleaner production system with a random defective rate for multiple products. Considering these, the model becomes a non-linear constraint problem. Based on different distribution functions of random defective rates, to eliminate the defective items from the system, five special cases for effective system management are considered. A non-linear optimization technique is utilised to solve the model and obtain the global optimum solution of cleaner production system with multiple products and a global optimum solution. Numerical examples, graphical representations, and sensitivity analysis are given to illustrate the model. Numerical studies prove that the cost related with a Kai square-distribution gives the least cost and cost related with a beta distribution gives the maximum cost, whereas the literature shows a triangular distribution gives the minimum cost.
Biswajit Sarkar; Bikash Koli Dey; Sarla Pareek; Mitali Sarkar. A single-stage cleaner production system with random defective rate and remanufacturing. Computers & Industrial Engineering 2020, 150, 106861 .
AMA StyleBiswajit Sarkar, Bikash Koli Dey, Sarla Pareek, Mitali Sarkar. A single-stage cleaner production system with random defective rate and remanufacturing. Computers & Industrial Engineering. 2020; 150 ():106861.
Chicago/Turabian StyleBiswajit Sarkar; Bikash Koli Dey; Sarla Pareek; Mitali Sarkar. 2020. "A single-stage cleaner production system with random defective rate and remanufacturing." Computers & Industrial Engineering 150, no. : 106861.
In this study one obtained the optimal decision of a retailer for the replenishment rate with selling-price and credit-period dependent demand to maximize the profit. A time-varying deterioration rate was considered for those products. A credit-period was offered by the retailer to the end customer to settle the whole payments. The aim of the model was to obtain the maximum profit for the retailer based model. A solution methodology with an algorithm was used to obtain the global optimum profit. An illustrative numerical example was given to test the practical applicability of the model. Numerical study indicated that the profit was at a maximum when the permissible delay-period for payment offered by the suppliers was lies between the permissible delay-time, and the cycle time, offered by the retailer.
Biswajit Sarkar; Bikash Koli Dey; Mitali Sarkar; Sun Hur; Buddhadev Mandal; Vinti Dhaka. Optimal replenishment decision for retailers with variable demand for deteriorating products under a trade-credit policy. RAIRO - Operations Research 2020, 54, 1685 -1701.
AMA StyleBiswajit Sarkar, Bikash Koli Dey, Mitali Sarkar, Sun Hur, Buddhadev Mandal, Vinti Dhaka. Optimal replenishment decision for retailers with variable demand for deteriorating products under a trade-credit policy. RAIRO - Operations Research. 2020; 54 (6):1685-1701.
Chicago/Turabian StyleBiswajit Sarkar; Bikash Koli Dey; Mitali Sarkar; Sun Hur; Buddhadev Mandal; Vinti Dhaka. 2020. "Optimal replenishment decision for retailers with variable demand for deteriorating products under a trade-credit policy." RAIRO - Operations Research 54, no. 6: 1685-1701.
This study explains about a serial smart production system where a single-type of product is produced. This system uses an unequally sized batch policy in subsequent stages. The setup cost is not always deterministic, it can be controllable and reduced by increasing the capital investment cost, and that the production rates in the system may vary within given limits across batches of shipments. Furthermore, as imperfect items are produced in long-run system, to clean the imperfectness autonomation policy is adopted for inspection, which make the process smarter. The shipment lot sizes of the deliveries are unequal and variable. In long-run production system, defective items are produced in “out-of-control” state. In this model, the defect rate is random with a uniform distribution which is clean from the system by autonomation. In addition, in the remanufacturing process, it is assuming that all defective products are repaired, and no defective products are scrapped. The main theme of developing this model is to determine the number of shipments and the optimal production lot size to adjust the production rates and decrease the total system cost under a reduced setup cost by considering the discrete investment and make a serial smart production system. A solution procedure along with an advanced algorithm was proposed for solving the model. Numerical examples with some graphical representations are provided to validate the model.
Mitali Sarkar; Li Pan; Bikash Koli Dey; Biswajit Sarkar. Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production? Mathematics 2020, 8, 1142 .
AMA StyleMitali Sarkar, Li Pan, Bikash Koli Dey, Biswajit Sarkar. Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production? Mathematics. 2020; 8 (7):1142.
Chicago/Turabian StyleMitali Sarkar; Li Pan; Bikash Koli Dey; Biswajit Sarkar. 2020. "Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?" Mathematics 8, no. 7: 1142.
The necessity of optimum safety stock is really essential for any smart production system. For this reason, the effect of autonomation policy makes a big difference with the basic traditional automation policy. Basically, for a long-run production system, a process may transfer to an ‘out-of-control’ state from an ‘in-control’ state due to labour problems, machinery problems, or any kind of energy problems. During this ‘out-of-control’ state, machines produced imperfect items instead of perfect items. As a result, an inspection is required to identify the imperfect ones. Until now, this inspection has been utilised by human beings through the traditional automation policy and inspection errors may occur. To perform an error-free inspection, an autonomation policy is examined in this model to detect imperfect items from the production process, which makes the process smarter. The defective rate is random and follows a certain distribution. A budget and a space constraints are adopted, which makes the model non-linear with a constraint problem. Contradictory to the existing literature, the demand is price- and quality-sensitive together in a smart production system. To solve this non-linear problem with an optimised value of backorders, number of delivery lots, safety factors, and collection rate, a non-linear optimisation technique (Khun–Tucker optimisation technique) is employed. A numerical example and sensitivity analysis are provided to illustrate the model. The result finds that the optimum autonomation policy can save work-in-process inventory at the optimum value of the decision variable in the proposed model.
Bikash Koli Dey; Sarla Pareek; Muhammad Tayyab; Biswajit Sarkar. Autonomation policy to control work-in-process inventory in a smart production system. International Journal of Production Research 2020, 59, 1258 -1280.
AMA StyleBikash Koli Dey, Sarla Pareek, Muhammad Tayyab, Biswajit Sarkar. Autonomation policy to control work-in-process inventory in a smart production system. International Journal of Production Research. 2020; 59 (4):1258-1280.
Chicago/Turabian StyleBikash Koli Dey; Sarla Pareek; Muhammad Tayyab; Biswajit Sarkar. 2020. "Autonomation policy to control work-in-process inventory in a smart production system." International Journal of Production Research 59, no. 4: 1258-1280.
Cost reduction for setup and improvement of processes quality are the main target of this research along with free minimal repair warranty for an imperfect production System. This paper deals with the effect of setup cost reduction and process quality improvement on the optimal production cycle time for an imperfect production process with free product minimal repair warranty. Here the production system is subject to a random breakdown from an controlled system to an out-of-control state. Shortages are fully backlogged. The main target to minimize the total cost by simultaneously optimizing the production run time, setup cost, and process quality. A solution algorithm with some numerical experiments are provided such as the proposed model can illustrate briefly. Sensitivity analysis section is decorated for the optimal solution of the model with respect to major cost parameters of the system are carried out, and the implications of the analysis are discussed.
Rekha Guchhait; Bikash Koli Dey; Shaktipada Bhuniya; Baishakhi Ganguly; Buddhadev Mandal; Raj Kumar Bachar; Biswajit Sarkar; Huiming Wee; Kripa Sindhu Chaudhuri. Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages. RAIRO - Operations Research 2020, 54, 251 -266.
AMA StyleRekha Guchhait, Bikash Koli Dey, Shaktipada Bhuniya, Baishakhi Ganguly, Buddhadev Mandal, Raj Kumar Bachar, Biswajit Sarkar, Huiming Wee, Kripa Sindhu Chaudhuri. Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages. RAIRO - Operations Research. 2020; 54 (1):251-266.
Chicago/Turabian StyleRekha Guchhait; Bikash Koli Dey; Shaktipada Bhuniya; Baishakhi Ganguly; Buddhadev Mandal; Raj Kumar Bachar; Biswajit Sarkar; Huiming Wee; Kripa Sindhu Chaudhuri. 2020. "Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages." RAIRO - Operations Research 54, no. 1: 251-266.
This model investigates the variable production cost for a production house; under a two-echelon supply chain management where a single vendor and multi-retailers are involved. This production system goes through a long run system and generates an out-of-control state due to different issues and produces defective items. This model considers the reduction of the defective rate and setup cost through investment. A discrete investment for setup cost reduction and a continuous investment is considered to reduce the defective rate and to increase the quality of products. Setup and processing time are dependent on lead time in this model. The model is solved analytically to find the optimal values of the production rate, safety factors, optimum quantity, lead time length, investment for setup cost reduction, and the probability of the production process going out-of-control. An efficient algorithm is constructed to find the optimal solution numerically and sensitivity analysis is given to show the impact of different parameters. A case study and different cases are also given to validate the model.
Bikash Koli Dey; Biswajit Sarkar; Sarla Pareek. A Two-Echelon Supply Chain Management With Setup Time and Cost Reduction, Quality Improvement and Variable Production Rate. Mathematics 2019, 7, 328 .
AMA StyleBikash Koli Dey, Biswajit Sarkar, Sarla Pareek. A Two-Echelon Supply Chain Management With Setup Time and Cost Reduction, Quality Improvement and Variable Production Rate. Mathematics. 2019; 7 (4):328.
Chicago/Turabian StyleBikash Koli Dey; Biswajit Sarkar; Sarla Pareek. 2019. "A Two-Echelon Supply Chain Management With Setup Time and Cost Reduction, Quality Improvement and Variable Production Rate." Mathematics 7, no. 4: 328.
This paper develops a sustainable integrated inventory model for maximizing profit with a controllable lead time, discrete setup cost reduction, and consideration of environmental issues. Contrary to the available literature, this paper considers a discrete setup cost for the vendor, thus making the integrated model sustainable. The customer’s demand is assumed to be selling-price dependent to increase the number of sales, and the lead time demand follows a Poisson distribution. The integrated model is used to optimized the total shipment number, volume of shipments, safety factor, investments, selling-price, and probability of moving between the “in-control” to “out-of-control” states. An algorithm is developed to obtain the numerical results. Numerical examples and sensitivity analyses are given to illustrate the model.
Bikash Koli Dey; Biswajit Sarkar; Mitali Sarkar; Sarla Pareek. An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment. RAIRO - Operations Research 2019, 53, 39 -57.
AMA StyleBikash Koli Dey, Biswajit Sarkar, Mitali Sarkar, Sarla Pareek. An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment. RAIRO - Operations Research. 2019; 53 (1):39-57.
Chicago/Turabian StyleBikash Koli Dey; Biswajit Sarkar; Mitali Sarkar; Sarla Pareek. 2019. "An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment." RAIRO - Operations Research 53, no. 1: 39-57.
Biswajit Sarkar; Arunava Majumder; Mitali Sarkar; Bikash Koli Dey; Gargi Roy. Two-echelon supply chain model with manufacturing quality improvement and setup cost reduction. Journal of Industrial & Management Optimization 2017, 13, 1085 -1104.
AMA StyleBiswajit Sarkar, Arunava Majumder, Mitali Sarkar, Bikash Koli Dey, Gargi Roy. Two-echelon supply chain model with manufacturing quality improvement and setup cost reduction. Journal of Industrial & Management Optimization. 2017; 13 (2):1085-1104.
Chicago/Turabian StyleBiswajit Sarkar; Arunava Majumder; Mitali Sarkar; Bikash Koli Dey; Gargi Roy. 2017. "Two-echelon supply chain model with manufacturing quality improvement and setup cost reduction." Journal of Industrial & Management Optimization 13, no. 2: 1085-1104.