A Conceptual Framework for Reverse Logistics Performance and Innovation

Green Supply Chain Management has been receiving a lot of attention in recent times. Attention on Reverse Logistics (RL) area has also been steadily growing. Reverse Logistics involves reduce-reuse-recycle as well as redesign, remanufacture, etc. It is a closed loop of the Supply Chain for value creation. Carter and Ellram (1998) discuss that Reverse Logistics can result in savings for an organization. Daugherty, Richey, Genchev, and Chen (2005) analyze where the resources in Reverse Logistics could be committed to achieve good Reverse Logistics Performance. The Automotive after-market in India is also in its nascent stages and has a huge scope for growth. Thus, a study in this area is definitely warranted. This paper gives a Conceptual framework for the RL Performance and Innovation in Automotive after-market with an emerging economy backdrop. The authors of this paper find fewer papers in these areas and this paper aims to fill this gap

Returned Product Acquisition Pricing by Adaptive Neuro Fuzzy Inference System

In recent years, reverse logistics have become increasingly important for the firms as a both environmental and economical approach. By collecting the returned products, firms realize to recover after kind of activities. In return products collection, due to the fact that each returned products have different functionality, determining the acquisition price of the used products is an important problem. For this reason, a pricing approach that can be used for collecting returned products is proposed in this study. Since the different product models can be exist and the acquisition price can be affected by the new product price, the acquisition price is predicted by the ratio of the new product price to acquisition price. In this study, the acquisition price ratio to new product price is modeled by the adaptive neuro fuzzy inference system and a case study is conducted for the used cell phones collection. Four phone models that have different release dates take into consideration with general appearance and functionality parameters. When the results are examined, the proposed method prediction's is pretty close to the expert view

Integration of mahalanobis-taguchi system and activity based costing in decision making for remanufacturing

Classifying components at the end of life (EOL) into remanufacture, repair or dispose is still a major concern to automotive industries. Prior to this study, no specific approach is reported as a guide line to determine critical crankpins that justifying economical remanufacturing process. Traditional cost accounting (TCA) has been used widely by remanufacturing industries but this is not a good measure of estimating the actual manufacturing costs per unit as compared to activity based costing (ABC). However, the application of ABC method in estimating remanufactured cost is rarely reported. These issues were handled separately without a proper integration to make remanufacturing decision which frequently results into uneconomical operating cost and finally the decision becomes less accurate. The aim of this work is to develop a suitable pattern recognition method for classifying crankshaft into three different EOL groups and subsequently evaluates the critical and non-critical crankpins of the used crankshaft using Mahalanobis-Taguchi System (MTS). A remanufacturability assessment technique was developed using Microsoft Excel spreadsheet on pattern recognition and critical crankpins evaluation, and finally integrates these information into a similar spreadsheet with ABC to make decision whether the crankshaft is to be remanufactured, repaired or disposed. The developed scatter diagram was able to recognize group pattern of EOL crankshaft which later was successfully used to determine critical crankpins required for remanufacturing process. The proposed method can serve as a useful approach to the remanufacturing industries for systematically evaluate and decide EOL components for further processing. Case study on six engine models, the result shows that three engines can be securely remanufactured at above 40% profit margin while another two engines are still viable to remanufacture but with less profit margin. In contrast, only two engines can be securely remanufactured due overcharge when using TCA. This inaccuracy affects significantly the overall remanufacturing activities and revenue of the industry. In conclusion, the proposed integration on pattern recognition, parameter evaluation and costing assists the decision making process to effectively remanufacture EOL automotive components as confirmed by Head of workshop of Motor Teknologi Industri Sdn. Bhd

Optimal production planning for a multi-product closed loop system with uncertain demand and return

We study the production planning problem for a multi-product closed loop system, in which the manufacturer has two channels for supplying products: producing brand-new products and remanufacturing returns into as-new ones. In the remanufacturing process, used products are bought back and remanufactured into as-new products which are sold together with the brand-new ones. The demands for all the products are uncertain, and their returns are uncertain and price-sensitive. The problem is to maximize the manufacturer\u27s expected profit by jointly determining the production quantities of brand-new products, the quantities of remanufactured products and the acquisition prices of the used products, subject to a capacity constraint. A mathematical model is presented to formulate the problem and a Lagrangian relaxation based approach is developed to solve the problem. Numerical examples are presented to illustrate the model and test the solution approach. Computational results show that the proposed approach is highly promising for solving the problems. The sensitivity analysis is also conducted to generate managerial insights

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time

Improving the efficiency of remanufacture through enhanced pre-processing inspection–a comprehensive study of over 2000 engines at Caterpillar remanufacturing, U.K.

Remanufacture, an industrial process to return used product to an “as-new” condition, is a key strategy in environmentally conscious manufacturing and waste management. However strategies to improve the efficiency of the process are hampered by a lack of remanufacturing-specific knowledge and tools. This paper presents the results of quantitative research, conducted in a Caterpillar Remanufacturing UK facility, to establish the relationship between pre-processing inspection levels and the subsequent remanufacturing process time for returned used products known as cores. It concludes that for components (i.e. cores) having either complex geometry (such as internal ports), a large number of sub-components or that are constructed from, or comprising of, multiple materials the remanufacturing process is shortened by increased inspection prior to processing. However, these benefits are currently limited by the amount of information that can be gained from the inspection methods used. The paper describes the practical use of these factors in a decision-making methodology for inspection and in a refined cost assessment tool

Analysis of Factors Influencing the Decisions over Purchasing Second-Hand Products

Second hand products are gaining more prominence in the present era of the world because there is an improvement in technology on a daily basis. This means that the products produced today will be outdated tomorrow and in order to go for an advanced version, there is a need to sell used products. The selling of second hand products makes today’s buyer to become a seller tomorrow, which are both profitable for the two parties. In this respects, there are certain factors influencing the purchase of these products considering the fact that they have been used before. These factors include; price, risk, market place and brand. Sometimes, we cannot say price is the only reason for purchasing these products since both rich and poor are now going for it. But definitely, price constitutes one of the main reasons because it is reasonable to buy a second hand product in good condition to perform the same task with the new product at a cheaper rate. Other influencing factors such as risk play a pivotal role as well because these products have been used before and they might be sold due to some faults, which could eventually make them useless for new buyers. The different roles played by these influencing factors have been well explained in this project using both primary and secondary data

A systems dynamics enabled real-time efficiency for fuel cell data-driven remanufacturing

Remanufacturing is a viable option to extend the useful life of an end-of-use product or its parts, ensuring sustainable competitive advantages under the current global economic climate. Challenges typical to remanufacturing still persist, despite its many benefits. According to the European Remanufacturing Network, a key challenge is the lack of accurate, timely and consistent product knowledge as highlighted in a 2015 survey of 188 European remanufacturers. With more data being produced by electric and hybrid vehicles, this adds to the information complexity challenge already experienced in remanufacturing. Therefore, it is difficult to implement real-time and accurate remanufacturing for the shop floor; there are no papers that focus on this within an electric and hybrid vehicle environment. To address this problem, this paper attempts to: (1) identify the required parameters/variables needed for fuel cell remanufacturing by means of interviews; (2) rank the variables by Pareto analysis; (3) develop a casual loop diagram for the identified parameters/variables to visualise their impact on remanufacturing; and (4) model a simple stock and flow diagram to simulate and understand data and information-driven schemes in remanufacturing