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 Product recovery aims to minimize the amount of waste sent to landfills by recovering materials and parts from old or outdated products by means of recycling and remanufacturing.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.     

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.     

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.     

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.     

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.     

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.     

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.     

An integrated framework for product line design for modular products: product attribute and functionality-driven perspective

The purpose of this research is to facilitate original equipment manufacturers operating in a single market segment to frame their product line design strategy that pertains to offering right product attributes with right attribute level in the right product profile within a market segment. Through this research, we attempt to establish a link between functional level design of product attributes with commercial objectives of the enterprise. Initially, by deriving the functional importance of product attribute levels of individual product attributes within a product profile, demand and functional importance data are generated. Utilising the function-based cost estimating framework and multi-linear regression methodology, we determine the cost and product development time coefficients for respective product attributes. Finally, a mixed integer quadratic programming-based mathematical formulation is developed that includes maximisation of product premium and minimisation of various costs as major objectives under the assumption that manufacturer seeks to offer optimal number of product profiles within the market segment. Employing the commercial solver LINGO, the integrated framework is solved. The entire framework is illustrated using the operator cabin of heavy construction machinery.     

Coordinated optimisation of platform-driven product line planning by bilevel programming

Product line planning (PLP) aims at an optimal combination of product feature offerings, suggesting itself to be a determinant decision for a company to satisfy diverse customer needs and gain competitive advantages. Fulfilment of planned product lines must make trade-offs between product variety and production costs. To balance the costs of product lines, manufacturers often adopt a product platform configuration (PPC) approach to redesign product and process platforms by adding new modules to the legacy platforms. The PPC is an effective means of providing product variety while controlling the manufacturing costs. The PLP and PPC problems have traditionally been investigated separately in the marketing research and engineering design fields. It is important to coordinate PLP and PPC decisions within a coherent optimisation framework. This paper proposes a bilevel mixed 0–1 nonlinear programming model to formulate coordinated optimisation for platform-driven product line planning. The upper level deals with the PLP problem by maximising the profit of an entire product line, whilst the lower level copes with the multiple product platforms optimisation for the optimal PPC in accordance with the upper level decisions of product line structure. To solve this bilevel programming model, a bilevel genetic algorithm is developed to find the optimal solution. A case study of coordinated optimisation between an automobile line and its product platforms is presented to demonstrate the feasibility and effectiveness of the proposed bilevel programming in comparison with a typical ‘all-in-one’ approach and a non-joint optimisation programming.     

Multi-objective lot splitting for a single product m-machine flowshop line

In this paper, the mean flowtime and the makespan objectives are simultaneously investigated in a single product, m-machine, flowshop system. For this purpose, an efficiency frontier approach is applied and an optimal algorithm for generating all efficient solutions is developed. A comprehensive computational experiment is performed for analyzing the tradeoff between the two objectives and evaluating the proposed algorithm performance. The most-balanced-solution, MinMax, is defined and recommended as a desirable alternative for either the flowtime or the makespan optimal solutions. Results show that when the system is optimized for either the mean flowtime or the makespan, a significant loss in the nonoptimized objective value is observed. On the other hand, adopting the MinMax solution obtains a close to optimal solution in both objectives.     

Analysis of flexible decision strategies for sustainability-focused green product recovery system

Identifying and analysing key decision variables that an organisation can opt for in order to initiate resource recovery from return activities and improve overall performance is a challenge. Therefore, to assist organisations which are involved in or about to initiate an effective recovery process, this paper provides guidelines to establish flexible decision strategies using the interpretive structural modelling (ISM) approach. This study has identified interrelationships between green variables such as supplier commitment, cost, regulations, etc. and has categorised relevant enablers. Further, variables such as capacity utilisation, customer satisfaction, energy consumption reduction, etc. are recognised as outcomes or results. After statistically verifying these variables, it has been inferred that driving enablers aid in promoting performance variables, while the result variables represent outcomes achieved via the driving variables. Further, using MICMAC analysis, a graphical categorisation of the variables is done on the basis of the impact on performance. Later prioritisation of variables having high driving power and low dependence is conducted. Inputs in the proposed model are taken through a case study conducted in the paper industry. The proposed model can be quite helpful and can act as a generic tool to achieve the desired performance improvement of green product recovery systems.     

An environmental friendly recovery production line of waste toner cartridges

Quantity of waste toner cartridges has been generated following the increasing demand for printer and duplicator. Waste toner cartridge contains abundant valuable metals, plastics as well as toxic residual toner. Therefore, the recovery of waste toner cartridges is a meaningful subject, not only from waste treatment but also from environment protection. This study proposed a mechanical production line for recovering waste toner cartridges. The recovery process involved shearing process, magnetic separation, and eddy current separation. The recovery rates of steel (magnet), toner, aluminum, and plastic were 98.4%, 95%, 97.5%, and 98.8%, respectively. The results of the comparison between the production line and full manual dismantling indicated that the production line succeed in recovering waste toner cartridges. In addition, the proposed production line is an efficient and environmental friendly way for recovering waste toner cartridges.