Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal

Disassembly process planning is an act of preparing detailed operation instructions for disassembling used or an end-of-life (EOL) product to recover or dispose of its constituent parts or subassemblies. The main decisions are: (a) disassembly level; (b) disassembly sequence; and (c) EOL options such as reuse, remanufacturing, recycling, incineration, landfill, etc. This study deals with the three decision variables simultaneously in the parallel disassembly environment for the objective of maximising the profit. Unlike previous studies, we consider practical constraints, i.e., reuse probability and environmental impacts of parts or subassemblies, sequence-dependent setup costs, regulation on recovery rate, and incineration capacity. To represent and solve the problem, we develop an extended AND/OR graph, and then suggest a two-phase algorithm. To show the effectiveness of the proposed algorithm, two case studies have been carried out on an automatic pencil and a telephone. Also, test results on other general product structures are reported.     

Disassembly line balancing using linear physical programming

Disassembly is the separation of a product into its constituent parts in a systematic way. It has gained importance recently due to its vital importance in product recovery. Cost-effective implementation of disassembly operation has a direct impact on the profitability of product recovery activities (recycling, remanufacturing etc.). Although it is possible to carry out disassembly operations in a disassembly station or in a disassembly cell, the highest productivity is achieved in a disassembly line. The output of a disassembly line can be maximised only if the line is balanced. A linear physical programming-based disassembly line balancing method is proposed in this study. This method was used to balance a mixed-model disassembly line and the effectiveness of the method was illustrated by analysing the results.     

Planning stability in a product recovery system

Recovery of used products is an issue of growing importance due to customer expectations and environmental regulation. As a consequence, companies need to adapt their material management taking into account inbound flows of used products. Corresponding inventory control models have been proposed in literature. In this paper we address the issue of planning stability in a product recovery context. To this end, we consider rolling horizon planning for a stock point facing stochastic demand and product returns. We analyze the impact of the return flow on planning stability and compare the system behaviour with a traditional production environment. We show that structural results derived for traditional inventory models remain valid in a product recovery context. Moreover we discuss counterintuitive effects resulting from interaction between planning stability and stock levels.     

Analysis of a product recovery system

The continuous growth in consumer waste in recent years has seriously threatened the environment. Environmentally conscious manufacturing and product recovery has become an obligation to the environment and to society. Many countries are contemplating regulations that force manufacturers to take back used products from consumers so that the components and materials retrieved from the products may be reused and/or recycled. We focus on a product recovery system in a remanufacturing system. Product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing. It should be considered when designing and managing the manufacturing systems. We propose a new analytical approach to evaluating the product recovery system with stochastic variability. This model applies the traditional inventory theory to the production/inventory management with consideration for disposal and return. The system is formulated by a discrete time Markov chain. It is composed of the states denoted by the number of the inventory, the transition probabilities between states and the costs associated with the transitions. Using the Markov analysis, we can calculate the total expected average cost per period exactly. Numerical examples are given to show the property of the management system and optimize the product recovery system.     

Disassembly line design with multi-manned workstations: a novel heuristic optimisation approach

As the first and the most time consuming step of product recovery, disassembly is described as the systematic separation of constituent parts from end-of-life products through a series of operations. In this context, designing and balancing disassembly lines are critical in terms of the efficiency of product recovery. Recent research on disassembly line balancing (DLB) has focused on classical stations where only one worker is allocated. However, such a line results in larger space requirement and longer disassembly lead time. In this paper, disassembly line balancing problem (DLBP) with multi-manned stations is introduced to the relevant literature as a solution to overcome these disadvantages. A mixed integer linear programming (MILP) model and two novel framework heuristic algorithms are developed to minimise the number of workers and workstations. MILP model has been applied to a dishwasher disassembly system. The application results indicate the superiority of establishing multi-manned stations over classical disassembly system design with single-worker stations with shorter disassembly lead time (80.9%) and line length (60.2%). Moreover, the proposed heuristics have been compared on newly generated test problems (instances) for DLBP. The results validate that the heuristics provide acceptable solutions in a reasonable amount of time even for large-sized problems.     

Improving cost effectiveness in an existing product line using component product platforms1

Previously, we introduced a new method for improving commonality in a highly customised, low volume product line using component product platforms. The method provides a bottom-up platform approach to redesign family members originally developed one-at-a-time to meet specific customer requirements. In this paper, we extend the method with an activity-based costing (ABC) model to specifically capture the manufacturing costs in the product line, including the cost associated with implementing a platform strategy. The valve yoke example is revisited in this paper, the customised ABC model is defined, two design strategy alternatives are addressed, and the new method is used to determine which alternative is better at resolving the trade-off between commonality, total cost, and product performance. The proposed method shows promise for creating a product platform portfolio from a set of candidate component platforms that is most cost-effective within an existing product line. The proposed method allows for arbitrary leveraging as it does not rely solely on the traditional vertical, horizontal, or beachhead strategies advocated for the market segmentation grid, and this is especially beneficial when applied to an existing product line that was developed one-at-a-time time such that artefact designs are inconsistent from one to another.     

Planning product disassembly for material recovery opportunities

This paper addresses an increasingly important aspect of product design and its relationship to life-cycle costing: disassembly for material recovery opportunities (MRO). MRO is defined as an opportunity to reclaim post-consumer products for recycling, remanufacturing and re-use. The authors have developed a methodology which can be used to identify and assess cost-effective characteristics of disassembly for the recovery of products. The central focus of this paper is aimed at improving the efficiency of the disassembly planning process and generating an optimal disassembly sequence. Four criteria are established to optimize the generation of the disassembly sequence: (1) material compatibility, (2) clustering for disposal, (3) concurrent disassembly operations, and (4( maximizing yield. In this paper we define the ‘disassemblability’ of a product as the ability to optimize the design and disassembly process for removal of specific pans or materials in a manner which will minimize costs. Steps have been taken to incorporate this methodology within a life-cycle analysis software tool (EDIT) to be used at the early concept stage of product design.     

An evolutionary approach for product line adaptation

A product line is rarely designed from scratch but usually evolves with products phased in and phased out. The adaptations of a product line and the associated changes in product mix and prices have complicated implications upon both market demand and manufacturing cost. This paper proposes an evolutionary approach to support coordinated decision-making among marketing, engineering and manufacturing regarding product line adaptation. A mixed logit discrete choice model and an activity based costing model are developed to quantify the demand and cost implications of product line adaptation, respectively. Product line adaptation is then formulated as a mixed integer non-linear programming problem. Given the coexistence of both discrete and continuous variables, a bi-level optimisation procedure combining genetic algorithm and differential evolution is developed for problem-solving. The proposed methodology is illustrated with an example of netbook product line design.     

Dynamic buy-back for product recovery in end-of-life spare parts procurement

The efficient supply of spare parts is of prime concern for original equipment manufacturers (OEM). While manufacturing the parent product, spare parts can be sourced efficiently by using existing manufacturing facilities. This situation completely changes once the original equipment manufacturer ceases production of the parent product. In addition to traditional spare parts sources in the form of final order and remanufacturing, the option to buy back parts or products provides a viable alternative in the end-of-life phase. This can prevent the OEM from fulfilling his spare parts availability obligation or increase his ability to remanufacture. Current practice in industry is, on the one hand, to offer trade-in campaigns to acquire functional products from customers by giving substantial discounts on a new-generation product. On the other hand, trade-in rebates are given when customers return their broken parts in exchange for spare parts. We propose the consideration of a third option, i.e. to buy back broken products in order to improve control of both demand for spare parts and supply of recoverable parts. This contribution seeks to assess the potential benefit of buy-back strategies in contrast to both traditional sourcing and trade-in campaigns for different settings regarding information availability and buy-back flexibility. For each situation, a MILP formulation is presented, and in a numerical study we analyse the circumstances under which the buy-back of broken products is especially beneficial for the OEM.     

Strategies for evaluating performance of flexibility in product recovery system

In view of the increasing business opportunities with changing customer attitudes and stricter legislations, the handling of returns has become a daunting challenge. The need for decision models for evaluating return performance has been observed in the academia and the corporate world. To improve return system performance, integrated flexible reverse enterprise systems have attracted attention from researchers as well as practitioners. This paper addresses these critical issues and proposes a novel integrated and Flexible recovery system decision model. The proposed model aims to facilitate enterprises in assessing their product recovery system capability, and in improving overall performance. The proposed model is a natural extension of several well-grounded policies for conventional reverse supply chains and can be verified on a simulation platform.     

A re-entrant line model for software product testing

In today’s competitive environment for software products, quality is an important characteristic. The development of large-scale software products is a complex and expensive process. Testing plays a very important role in ensuring product quality. Improving the software development process leads to improved product quality. We propose a queueing model based on re-entrant lines to depict the process of software modules undergoing testing/debugging, inspections and code reviews, verification and validation, and quality assurance tests before being accepted for use. Using the re-entrant line model for software testing, bounds on test times are obtained by considering the state transitions for a general class of modules and solving a linear programming model. Scheduling of software modules for tests at each process step yields the constraints for the linear program. The methodology presented is applied to the development of a software system and bounds on test times are obtained. These bounds are used to allocate time for the testing phase of the project and to estimate the release times of software.     

Assessing comparative production efficiencies for product line management

Product line management involves product expansion or elimination depending on various factors, for example, production processes and demands in the market. This study focuses on measuring product performance for a firm’s product line management, using parametric and non-parametric approaches. First, we choose variables related to the production and demand of products and assess the comparative performance of product groups and individual products using data envelopment analysis (DEA). Second, we attempt to detect possible performance differences among the product groups using one-way analysis of variance. Third, we identify the sources of inefficiency using appropriate DEA scores and offer some managerial insights. Last, we try to confirm the determinants of product performance using Tobit regression analysis. The major contribution of this study is the use of a novel approach for product line management by measuring the performance of product groups and individual products using pertinent variables. The approach used in this study is applicable to various manufacturing and service industries. The limitations of this study are the number of product groups selected and examination of performance using cross-sectional data.     

Improving software product line using an ontological approach

Software product line (SPL) is an emergent strategy for generating software products. The variability and commonality of SPL is illustrated by feature models (FMs). The quality of software products relies on the correctness of SPL. The overall benefits of software product line engineering (SPLE) are reduced by various kinds of defects such as dead features and false optional features in an FM. These defects can be inherited in the software products built from a defective product line model (PLM). In this paper, the problem of enhancing the quality of software products derived from SPLE is handled. An ontological based approach is proposed following first-order logic (FOL) rules to identify defects namely dead features and false optional features. The classification of cases for these defects in FMs that represent variability of SPL is defined. The presented approach has been explained with the help of an FM derived from the standard case in product line (PL) community. The initial empirical evaluation of the proposed approach analyses 35 FMs with different sizes. The results obtained exhibit that the proposed approach is accurate, effective, scalable up to 200 features and therefore improves SPL.     

The value of information systems for product recovery management

This article sheds light on the role of information systems in product recovery management. We first develop analytical models and then provide a numerical example to determine under what conditions investments in Information-intensive Product Recovery Systems (IPRS) are economically justifiable for manufacturers and when policy-makers need to consider facilitating their implementation. The results of the analytical models indicate that the recovery network (collection) structure and product characteristics determine if precision improvements or increased sorting speed associated with IS investments will lead to higher profit gains. Manufacturers should carefully assess conflicting impacts of current manufacturing and recycling technology trends on the value of IPRS. Implementing IPRS might end up reducing manufacturers' profits under a highly time efficient decentralised collection structure. We show that negotiations with competitors about IPRS implementation may lead to a win–win situation and allow consumers to enjoy the lowest product price if the binding force of the agreement is strong. Otherwise, some manufacturers follow free-rider strategies. This article has immediate application to manufacturers' IS strategy and to government policy-makers considering investing in and/or structuring product recovery closed-loop supply chain processes within their jurisdictions. It also opens a potential stream of research concerning the role of IPRS to automate, informate and transform closed-loop supply chains for eco-efficiency.     

A production scheduling plan for a diversified product line

This paper describes a production control plan which may be -used in a shop whose product line consists of numerous items which vary extensively in their demand pattern.

The plan is capable of: (a) stabilizing production by allowing inventories to fluctuate with moderate demand fluctuations; (b) minimizing inventories of finished goods while providing protection against serious Btockout; (c) detecting significant changes in demand patterns and revising production schedules accordingly; and (d) scheduling production economically.

Employing several well-known concepts, such as the control limits principle used in quality control, the plan considers simultaneously forecasted demand, forecast error, inventory position and shop capacity to arrive at production decisions. For this purpose, control limits are applied to both demand and inventory, and production is stabilized with a simple production smoothing procedure. Simulation results, based on data taken from a medium size production shop, demonstrate the plan effectiveness.

Overall, the paper emphasizes operational features rather than theoretical concepts, However, it is shown that the plan is amenable to generalized treatment.