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Application of Renewable Energy in Production and Supply Chain Management

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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 24677

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Prof. Dr. Biswajit Sarkar

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Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, Republic of Korea
Interests: supply chain management; optimization; artificial intelligence; smart production; mathematical modelling; inventory management; smart logistics; biomathematics; circular economy; sustainability; renewable energy
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Special Issue Information

Dear Colleagues,

Today, the application of renewable energy is increasing in supply chain management (SCM). Different forms of energy are consumed during the manufacturing and retailing of products, which includes electricity generation, air and water heating/cooling, transportation, and some other energy services. This energy consumption increases when the system is based on a smart supply chain. The establishment of the energy transition to renewable energy sources has become one of the important global development in recent times, resolving the serious problem of sustainable energy supply in SCM.

Renewable energy is collected from some resources that are naturally replenished on a human timescale such as solar, wind, rain, tides, waves, and geothermal heat. In comparison to other energy sources, renewable energy resources exist over wide geographical areas. The development of inexpensive, vast, and clean solar energy technologies have massive long-term benefits. A slow flowing stream of water or moderate sea swell can yield considerable amounts of energy. Airflows can be used to run wind turbines. These renewable energy resources increase system’s energy security, enhance sustainability, reduce pollution, decrease the cost of mitigating climate change, and keep fossil fuel at lower prices. These advantages have a global impact on environment. Hence, shifting energy consumption from fossil sources to renewables is a main objective of SCM and smart supply chain management (SSCM) to make it an energy-efficient supply chain management (EESCM). Thus, the aim of this proposal is to save energy in several ways under the framework of SCM.

Prof. Dr. Biswajit Sarkar
Guest Editor

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Keywords

Green supply chain management with renewable energy
Application of energy in production system
Renewable energy in inventory management
Energy-efficient supply chain management
Energy efficiency and energy consumption
Sustainable energy and energy saving

Published Papers (7 papers)

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Research

32 pages, 4025 KiB

Open AccessArticle

Effect of Electrical Energy on the Manufacturing Setup Cost Reduction, Transportation Discounts, and Process Quality Improvement in a Two-Echelon Supply Chain Management under a Service-Level Constraint

by Irfanullah Khan, Jihed Jemai, Han Lim and Biswajit Sarkar

Energies 2019, 12(19), 3733; https://doi.org/10.3390/en12193733 - 29 Sep 2019

Cited by 23 | Viewed by 3252

Abstract

The need for efficient electrical energy consumption has greatly expanded in the process industries. In this paper, efforts are made to recognize the electrical energy consumption in a two-echelon supply chain model with a stochastic lead-time demand and imperfect production, while considering the distribution free approach. The initial investments are made for quality improvement and setup cost reduction, which ultimately reduce electrical energy consumption. The inspection costs are considered in order to ensure the good qualities of the product. Centralized and decentralized strategies are used to analyze the proposed supply chain model. The main objective of this study is to reduce the overall cost through efficient electrical energy consumption in supply chain management by optimizing the lot size, the number of shipments, the setup cost, and the failure rate. A quantity-based transportation discount policy is applied to reduce the expected annual costs, and a service-level constraint is incorporated for the buyer to avoid a stockout situation. The impact of the decision variables on the expected total costs is analyzed, and sensitivity analysis is carried out. The results show a significant reduction in overall cost, with quality improvement and setup cost reduction ultimately reducing electrical energy consumption. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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27 pages, 1063 KiB

Open AccessArticle

Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption

by Iqra Asghar, Biswajit Sarkar and Sung-jun Kim

Energies 2019, 12(16), 3179; https://doi.org/10.3390/en12163179 - 19 Aug 2019

Cited by 12 | Viewed by 3154

Abstract

Expensive power cost is a significant concern in today’s manufacturing world. Reduction in energy consumption is an ultimate measure towards achieving manufacturing efficiency and emissions control. In the existing literature of scheduling problems, the consumption of energy is considered uncertain under the dimensions of uncertain demand and supply. In reality, it is a random parameter that also depends on production capacity, manufacturing technology, and operational condition of the manufacturing system. As the unit production cost varies with production rate and reliability of the manufacturing system, the energy consumption of the system also varies accordingly. Therefore, this study investigated an unreliable manufacturing system under stochastic production capacities and energy consumption. A stochastic production–inventory policy is developed to optimize production quantity, production rate, and manufacturing reliability under variable energy consumption costs. As energy consumption varies in different operational states of manufacturing, we consider three specific states of power consumption, namely working, idle, and repair time, for an integrated production–maintenance model. The considered production system is subjected to stochastic failure and repair time, where productivity and manufacturing reliability is improved through additional technology investment. The robustness of the model is shown through numerical example, comparative study, and sensitivity analysis of model parameters. Several graphical illustrations are also provided to obtain meaningful managerial insights. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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19 pages, 803 KiB

Open AccessArticle

An Application of Time-Dependent Holding Costs and System Reliability in a Multi-Item Sustainable Economic Energy Efficient Reliable Manufacturing System

by Mitali Sarkar, Sungjun Kim, Jihed Jemai, Baishakhi Ganguly and Biswajit Sarkar

Energies 2019, 12(15), 2857; https://doi.org/10.3390/en12152857 - 25 Jul 2019

Cited by 18 | Viewed by 2466

Abstract

Sustainable efficient energy is the key factor of any sustainable manufacturing system. This study addresses a multi-item sustainable economic energy efficient reliable manufacturing quantity (MSEEERMQ) model. The manufacturing system produces defective products during long-runs, where those products may be reworked under the optimum effect of energy and carbon footprint with some costs. As all products are not sold immediately, the holding cost increases based on time. The management decides the system design variable to reduce energy consumption cost and increase system reliability under some time-dependent holding costs, and the optimum energy such that the maximum profit of the production model is obtained with a system reliability as a decision variable. The inflation and time-value of money are considered to calculate the cost of the production model under efficient energy. Using control theory, an Euler–Lagrange method is employed to obtain the sustainable critical path, which gives the optimal solution of the model. There are two lemmas to prove the global optimal solution of the model through the control theory. There is an illustrative example to test the model. Under different conditions there are other two examples with graphical representation and sensitivity analysis. Numerical studies reveal that maximum profit is obtained at the optimal value of the decision variable. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

27 pages, 3713 KiB

Open AccessFeature PaperArticle

Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption

by Jihed Jemai and Biswajit Sarkar

Energies 2019, 12(14), 2789; https://doi.org/10.3390/en12142789 - 19 Jul 2019

Cited by 15 | Viewed by 4109

Abstract

The perishability of blood platelets complicates the management of their supply chain. This paper studies the impact of energy consumption and carbon emissions of transportation activities in a blood platelet supply chain. Energy consumption and carbon emissions vary significantly, and the effective location-allocation of blood facilities is a key strategy for the optimal use of energy. The total cost of the supply chain for perishable products is minimized when energy consumption is optimized. The proposed model is too complex to be solved with existing methodologies; therefore, mathematical tools are used to solve it. A numerical experiment is carried out to validate the proposed model, and graphical representations are presented for better visualization of the study’s outcomes. The results of the numerical studies confirm that the selected locations of blood facilities are optimal for the maximization of energy efficiency and minimization of the total cost. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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16 pages, 365 KiB

Open AccessArticle

Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management

by Mitali Sarkar and Biswajit Sarkar

Energies 2019, 12(11), 2059; https://doi.org/10.3390/en12112059 - 29 May 2019

Cited by 13 | Viewed by 3583

Abstract

A smart production system is essential to produce complex products under the consumption of efficient energy. The main ramification of controllable production rate, amount of production size, and safety stocks is simultaneously optimized under proper utilization of energy within a smart production system with a random breakdown of spare parts. Due to the random breakdown, a greater amount of energy may be used. For this purpose, this study is concerned about the optimum safety stock level under the exact amount of energy utilization. For random breakdown, there are three cases as production inventory meets the demand without utilization of the safety stock, with using of the safety stock, and consumed the total safety stock amount and facing shortages. After the random breakdown time, the smart production system may move to an out-of-control state and may produce defective items, where the production rate of defective items is a random variable, which follows an exponential distribution. The total cost is highly nonlinear and cannot be solved by any classical optimization technique. A mathematical optimization tool is utilized to test the model. Numerical study proves that the effect of energy plays an important role for the smart manufacturing system even though random breakdowns are there. it is found that the controllable production rate under the effect of the optimum energy consumption really effects significantly in the minimization cost. It saves cost regarding the corrective and preventive maintenance cost. The amount of safety stock can have more support under the effect of optimum energy utilization. The energy can be replaced by the solar energy. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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18 pages, 1207 KiB

Open AccessArticle

Effects of Carbon-Emission and Setup Cost Reduction in a Sustainable Electrical Energy Supply Chain Inventory System

by Umakanta Mishra, Jei-Zheng Wu and Anthony Shun Fung Chiu

Energies 2019, 12(7), 1226; https://doi.org/10.3390/en12071226 - 29 Mar 2019

Cited by 19 | Viewed by 3943

Abstract

This article develops a sustainable electricity supply chain mathematical model that assumes linear price-dependent customer demands where the price is a decision variable under setup cost and carbon emission. The sustainable electrical supply chain system contained: (a) power generation; (b) transmission substations; (c) distribution substations; and (d) customer. The production rates depend on the demand rate, and demand for electricity by the customers is dependent on the price of electricity where the electrical energy was generated and transmitted through multiple substations to customers. Moreover, we considered that the capacities of transmission rates, power generation, and distances in between two stations are associated with the distribution costs and transmission cost. Here, we used the theory of inventory to develop a new model and suggested a procedure to deduce an optimal solution for this model. Finally, a numerical example and sensitivity analysis are employed to illustrate the present study and with managerial insights. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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21 pages, 3613 KiB

Open AccessArticle

Effect of Energy and Failure Rate in a Multi-Item Smart Production System

by Mitali Sarkar, Biswajit Sarkar and Muhammad Waqas Iqbal

Energies 2018, 11(11), 2958; https://doi.org/10.3390/en11112958 - 30 Oct 2018

Cited by 16 | Viewed by 3062

Abstract

To form a smart production system, the effect of energy and machines’ failure rate plays an important role. The main issue is to make a smart production system for complex products that the system may produce several defective items during a long-run production process with an unusual amount of energy consumption. The aim of the model is to obtain the optimum amount of smart lot, the production rate, and the failure rate under the effect of energy. This study contains a multi-item economic imperfect production lot size energy model considering a failure rate as a system design variable under a budget and a space constraint. The model assumes an inspection cost to ensure product’s quality under perfect energy consumption. Failure rate and smart production rate dependent development cost under energy consumption are considered, i.e., lower values of failure rate give higher values of development cost and vice versa under the effect of proper utilization of energy. The manufacturing system moves from in-control state to out-of-control state at a random time. The theory of nonlinear optimization (Kuhn–Tucker method) is employed to solve the model. There is a lemma to obtain the global optimal solution for the model. Two numerical examples, graphical representations, and sensitivity analysis of key parameters are given to illustrate the model. Full article

(This article belongs to the Special Issue Application of Renewable Energy in Production and Supply Chain Management)

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