Carbon-emission and waste reduction of a manufacturing-remanufacturing system using green technology and autonomated inspection

Environmental-friendly technology helps to reduce waste and carbon emissions of an imperfect production system. In general, the defective products generated during the “out-of-control” state are treated as waste. The single-stage manufacturing-remanufacturing system effectively depletes such defective spare parts within the same cycle but causes a tremendous amount of carbon. In such a circumstance, green technology to reduce carbon emissions is highly recommended. Also, the autonomated inspection makes defective detection more reliable and is ultimately helpful for waste reduction. Hence, in this study, we optimize the production plan along with the investments for applying green technology and autonomated inspection in an assembled product manufacturing-remanufacturing system. The numerical result shows that the appropriate green technology decreases carbon emissions up to 2.81% and autonomated inspection reduces the waste up to 2.37%, along with a reduction of entire production cycle cost up to 18.26%. In addition, the setup cost reduction is considered due to the characteristics of assembled product production

A Two-Echelon Supply Chain Management With Setup Time and Cost Reduction, Quality Improvement and Variable Production Rate

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

Optimal Decisions on Greenness, Carbon Emission Reductions, and Flexibility for Imperfect Production with Partial Outsourcing

Global emphasis on sustainable development is widespread, with industries playing a pivotal role in advancing global sustainability within the business and retail sectors. Consumer awareness of environmental concerns, such as pollution, prompts a focus on product biodegradability and eco-friendliness. Consequently, customers are drawn to products with higher green credentials. This study delves into the effectiveness of green attributes in retail industries, exploring the optimization of profit through a variable production rate and variable unit production cost, considering the selling price and the demand dependent on the product’s green level. In the long run, production systems may shift to an “out-of-control” state, resulting in the random production of imperfect items that must be remanufactured to maintain the industry’s positive brand image. To mitigate the impact of defective items, the industry opts to partially outsource a percentage of items, preventing shortages. However, this complex retailing system generates a significant amount of carbon emissions. This study introduces investments aimed at reducing carbon emissions to address this issue. In contrast with the existing literature, a green-level-dependent unit raw material cost is considered here for variable unit production cost. Ultimately, this study seeks to maximize the overall system’s profit by optimizing the selling price, order quantity, production rate, green level, and carbon emission reduction investments. The classical optimization technique is utilized to obtain analytic optimum results for the decision variables and total profit. Special cases and sensitivity analyses illustrate the real-world applicability and impact of green levels. Numerical findings indicate that considering the product’s green-level-dependent demand and unit production rate is 22.44% more beneficial than nongreen products, partial outsourcing provides a 1.28% advantage, and flexibility in the production rate yields a 69.60% benefit over traditional systems without green elements. Additionally, technological investments to reduce carbon emissions result in a notable reduction of up to 4.53%

Autonomated Inspection Policy for Smart Factory—An Improved Approach

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

A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand

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

Advance sustainable inventory management through advertisement and trade-credit policy

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

A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand

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

An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling price dependent demand, and investment

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

Intelligent servicing strategy for an online-to-offline (O2O) supply chain under demand variability and controllable lead time

With the advancement of technologies, industries tries to adopt the advantages of the technology. Customers are busy in their daily life, and the online platform is the best option for retail, whereas traditional customers still prefer to visit the retail shop. Few customers choose the product online but buy it offline or vice-versa. Owing to all those circumstances, current study focuses on an intelligent dual channel (online-to-offline) strategy in industry to arrange the optimal services for customers. The selling price of the product vary with different channel, which helps to determine the demand of product for entire supply chain. Two important factors, backorder and lead-time are examined precisely through marginal value which helps to arrange optimal service and calculate the exact profit. The profit for a centralized and decentralized case are computed for both the players. Some propositions are developed to prove the global optimality. Numerical results prove that a centralized case provides 7.77% better profit than a decentralized case due to bonding between the players

Optimal replenishment decision for retailers with variable demand for deteriorating products under a trade-credit policy

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