This paper deals with the application of exact methods in disassembly sequencing subjected to sequence dependent costs to the development of heuristics. Application of exact methods is restricted to fairly simple products, because CPU time tends to increase exponentially with product complexity, which makes these methods inappropriate for complex products. One has to rely on heuristic methods that typically require a CPU time that polynomially increases with product complexity. As these methods typically return suboptimal solutions, a reliable benchmark is required that can be found in exact solutions. This application is demonstrated on a complex product with an extensive search space. It is demonstrated that a heuristic can be developed that generates a set of extremely good suboptimal solutions.

In recent decades, regulations and markets have been exerting pressure on designers and manufacturers to take more responsibility for the environmental impacts of their products throughout their life cycles. The problem of finding the disassembly sequence represents one of the major challenges when attempting to close product life cycles by carrying out reuse, recycling and remanufacturing practices. Many different techniques have been used to deal with this problem, varying from exact to heuristic solutions. So far, however, not much effort has gone into measuring and comparing the efficiency of this wide set of techniques. This is partly due to the difficulties of getting a wide population of real products, belonging to different industries and with different degree of complexity that might constitute a representative population for carrying out this kind of task. In this paper, a generator of complex products is presented that is able to build up products with hundreds of components joined by different kinds of joints in such a way that a theoretical “good” disassembly sequence is always known. The efficiency of different methods for general products can thus be easily compared. The performance of a Scatter Search algorithm is tested as an example of its application in this case.

Disassembly, as the process of systematic removal of desirable constituent parts from an assembly, is of growing importance due to the increasing environmental and economic pressures. Designing and improving disassembly process towards a more economic manner is worthwhile investigating. This paper extends our previous work on human factors in disassembly. More specifically, a Fuzzy Petri Net (FPN) is proposed to mathematically model uncertainties in the disassembly process due to the variations in operator skill level and product condition. An adaptive fuzzy system is further developed for the decision-making in disassembly process planning (DPP), where a learning mechanism is engaged to monitor the quality of various parameter estimates and exploit the past “knowledge” regarding uncertainties. This idea is exemplified through the disassembly of a discarded product with three components.

The valorization rate improvement depends on the product disassembly characteristics. So, researchers develop and implement the Design for Disassembly (DfD) methodology to increase the valorization. The design process of technical products is critical to define the End of Life (EoL) disassembly characteristics of a product. It is the reason why several tools have been developed to evaluate the product disassembly at the end of the design process, when all product characterizations are defined. Nevertheless, it appears that the product disassembly improvement cannot be possible without a real redesigning of the product. In fact, all the existing tools don’t take into account the influence of design parameters on the disassembly results; they focus on the future disassembly process. In previous studies, we have shown that the conceptual design is the most important phase to integrate disassembly constraints in design process. But, this design phase is not addressed by current approach of DfD. We also note that a systematic methodology, which incorporates disassembly evaluation earlier in a design process, is absent. In this paper, we present our proposition concerning a methodological approach to design product easy to disassemble. In our approach, we use a Conceptual Disassembly Model (CDM) to help designers to consider disassembly. A case study is presented to understand the approach and to illustrate our purpose.

Selection of an optimal disassembly sequence is essential for the efficient processing of a product at the end of its life. Disassembly sequences are listings of disassembly actions (such as the separation of an assembly into two or more subassemblies, or removing one or more connections between components). Disassembly takes place in remanufacturing, recycling, and disposal with a disassembly line being the best choice for automation. In this paper, the disassembly sequencing problem is solved for a cell phone case on a disassembly line, seeking a sequence which is feasible, minimizes the number of workstations (and hence idle times), provides for early removal of high demand/value parts, provides the removal of parts that lead to the access of greatest number of still-installed parts, and early removal of hazardous parts as well as for the grouping of parts for removal having identical part removal directions. Since finding the optimal sequence is computationally intensive due to factorial growth, a heuristic method is used taking into account various disassembly-specific matters. Using the experimentally determined precedence relationships and task times of a real-world cell phone, a MATLAB program is designed and a sequencing solution is generated. Finally, Design for Disassembly (DFD) improvements are recommended with respect to environmentally conscious manufacturing.

Disassembly takes place in remanufacturing, recycling, and disposal with a line being the best choice for automation. The disassembly line balancing problem seeks a sequence which: minimizes workstations, ensures similar idle times, and is feasible. Finding the optimal balance is computationally intensive due to factorial growth. Combinatorial optimization methods hold promise for providing solutions to the disassembly line balancing problem, which is proven to belong to the class of NP-complete problems. Ant colony optimization, genetic algorithm, and H-K metaheuristics are presented and compared along with a greedy/hill-climbing heuristic hybrid. A numerical study is performed to illustrate the implementation and compare performance. Conclusions drawn include the consistent generation of optimal or near-optimal solutions, the ability to preserve precedence, the speed of the techniques, and their practicality due to ease of implementation.

The use of personal computers (PCs) continues to increase every year. According to a 1999 figure, 50 percent of all US households owned PCs, a figure that continues to rise every year. With continuous development of sophisticated software, PCs are becoming increasingly powerful. In addition, the price of a PC continues to steadily decline. Furthermore, the typical life of a PC in the workplace is approximately two to three years while in the home it is three to five years. As these PCs become obsolete, they are replaced and the old PCs are disposed of. It is estimated that between 14 and 20 million PCs are retired annually in the US. While 20 to 30% of the units may be resold, the others are discarded. These discards represent a significant potential source of lead for the waste stream. In some communities, waste cathode ray tubes (CRTs) represent the second largest source of lead in the waste stream after vehicular lead acid batteries. PCs are, therefore, not suitable for dumping in landfills. Besides, several components of a PC can be reused and then there are other valuable materials that can also be harvested. And with the advent of product stewardship, product recovery is the best solution for manufacturers. Disassembly line is perhaps the most suitable set up for disassembling PCs. However, planning and scheduling of disassembly on a disassembly line is complicated. In this paper, we discuss some of the complications including product arrival, demand arrival, inventory fluctuation and production control mechanisms. We then show how to overcome them by implementing a multi-kanban mechanism in the PC disassembly line setting. The multi-kanban mechanism relies on dynamic routing of kanbans according to the state of the system. We investigate the multi-kanban mechanism using simulation and demonstrate that this mechanism is superior to the traditional push system in terms of controlling the system’s inventory while maintaining a decent customer service level.

In this paper we present a dynamic kanban (pull) system specifically developed for disassembly lines. This type of kanban system is much more complex than the traditional kanban system used in assembly lines. For instance, unlike the assembly line where the external demand occurs only at the last station, the demands in the disassembly case also occur at any of the intermittent stations. The reason is that as a product moves on the disassembly line, various parts are disassembled at every station and accumulated at that station. Therefore, there are as many demand sources as there are number of parts. We consider a case example involving the end-of-life products. Based on the precedence relationships and other criteria such as hazardous properties of the parts, we balance the disassembly line. The results of the disassembly line-balancing problem (DLBP) are used as input to the proposed dynamic kanban system for disassembly line (DKSDL). We compare the performance of the DKSDL to the modified kanban system for disassembly line (MKSDL), which was previously introduced by the authors. We show, via simulation, that the DKSDL is far superior to MKSDL considered.

Environmentally responsible manufacturing is concerned with minimizing the environmental impact of products from development to end-of-life disposal or remanufacture. Environmental pressures from customers, regulation, legislation and competition have made organizations more aware of the impact that products have on the natural environment. This study focuses on environmental concerns during the early stages of product design. We examine these concerns with a specific focus on the involvement of supply management personnel, inter-organizational supplier relationships and a determination of how environmental issues affect supplier selection and supply base management. The literature on environmental supplier and purchasing involvement in product development and environmental supplier selection criteria and codes of conduct is reviewed. Following this, secondary data from the websites of environmentally proactive organizations will be gathered to examine what type of tracking is used for suppliers. Finally, discussions with proactive organizations will be presented during the conference that explore the role of supply management personnel in capturing, measuring, quantifying and reporting on the environmental costs and benefits associated with its suppliers. This research provides insights into how the involvement of supply management can improve the environmental performance outcomes of an organization.

Today, since customers are able to obtain similar-quality products for similar prices, the lead time has become the only preference criterion for most of the consumers. Therefore, it is crucial that the lead time, i.e., the time spent from the raw material phase till the manufactured good reaches the customer, is minimized. This issue can be investigated under the title of Supply Chain Management (SCM). An efficiently managed supply chain can lead to reduced response time for customers. To achieve this, continuous observation of supply chain efficiency, i.e., a constant performance evaluation of the current SCM is required. Widely used conventional performance measurement methods lack the ability to evaluate a SCM since the supply chain is a dynamic system that requires a more thorough and flexible performance measurement technique. Balanced Scorecard (BS) is an efficient tool for measuring the performance of dynamic systems and has a proven capability of providing the decision makers with the appropriate feedback data. In addition to SCM, a relatively new management field, namely reverse supply chain management (RSCM), also necessitates an appropriate evaluation approach. RSCM differs from SCM in many aspects, i.e., the criteria used for evaluation, the high level of uncertainty involved etc., not allowing the usage of identical evaluation techniques used for SCM. This study proposes a generic Balanced Scorecard to measure the performance of supply chain management while defining the appropriate performance measures for SCM. A scorecard prototype, ESCAPE, is presented to demonstrate the evaluation process.

The need for sustainable product end-of-life management technologies is critical in today's globally competitive environment. The ever-increasing environmental consciousness of consumers and strictness in legislative regulations necessitate more prudent product decisions. The ability to make sound decisions on which product end-of-life management technologies to adopt is crucial to achieving sustainability of the product systems. It is essential that effective assessments of these technologies for future investment and applications indicate the total economic, environmental and social impacts of each option as well as the trade-offs between the various product end-of-life management technologies. The tendency in modeling this decision scenario is to base the formulation and the analysis on crisp, deterministic, and precise data. The product end-of-life management decision environment is however characterized by a mix of crisp and linguistically expressed parameters, most of which are uncertain in nature. Furthermore, the decision makers are interested in selecting an option that both satisfies certain minimum requirements and maximize their utility from a set of feasible alternatives. The goal of this study therefore is to develop a simple, efficient procedure that provides the manufacturing and allied industry with the ability to assess and evaluate the sustainability of remanufacturing and related technologies based on lifecycle thinking. This methodology, termed "product lifecycle extension techniques selection (PLETS) model," is a hybrid of fuzzy logic and a number of multi-attribute decision making models. It can be used to determine the remanufacturability of each product. In addition, it can also be employed to compare the economic, environmental and social sustainability of the feasible set of the product end-of-life management technologies being considered. The proposed methodology is illustrated with an example of end-of-life management for a peanut-shelling machine.

The designing of a reverse supply chain must involve selection of collection centers and recovery facilities that have sufficient success potentials. These success potentials depend heavily on the participation of the following three important groups who have multiple, conflicting, and incommensurate criteria for evaluation, and so, the potentials must be evaluated based on the maximized consensus among those groups: (i) Consumers (whose primary concern is convenience), (ii) Local government officials (whose primary concern is environmental consciousness), and (iii) Supply chain company executives (whose primary concern is profit). In this paper, we propose a three-phase multi-criteria group approach to select collection centers as well as recovery facilities, of sufficient success potentials. In the first phase of the approach, we identify important criteria for evaluation of the alternatives (collection centers as well as recovery facilities) by each of the above three groups. In the second phase, we give weights to the criteria of each group using the eigen vector method, and then, employ the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to find the success potential of each alternative, as evaluated by that group. Then, in the third and final phase, we use Borda’s choice rule that, for each alternative, combines individual success potentials into a group success potential.

It is difficult to obtain information regarding compositions and remaining life periods of used products. Hence, they often undergo partial or complete disassembly for subsequent re-processing (remanufacturing and/or recycling). However, researchers are now studying sensor embedded products (SEPs), the composition and remaining life of which can be obtained at the end of their use from sensors. This paper addresses decision-making regarding the futurity of an SEP at its end of use: whether to disassemble it for subsequent recycling/remanufacturing or to repair it for subsequent sale on a second-hand market. We identify some important factors that must be considered before making a decision. Using a numerical example, we propose a simple approach that employs Bayesian updating and fuzzy set theory to aid the decision-making process.

In this paper, we consider the problem of determining the optimal number of returned products to disassemble to fulfill the demand for a specified number of parts. This is known as the disassembly-to-order (DTO) problem. The deterministic yield version of this problem has been addressed in the literature. Recently, the stochastic yield version of this problem with a single objective has also been reported in the literature. In this paper, we extend the methodology to include multiple objectives. To this end, we model the DTO problem using integer goal programming. The stochastic problem is solved by transforming it into its deterministic equivalent problem. This conversion is accomplished by considering the specific structures of the products with one core and one part (“one-to-one structure”) and apply it to handle the products with one core and multiple parts (“one-to-many structure”). For these special cases it is possible to solve the stochastic problem analytically so that valuable insights can be gained by comparing the stochastic and deterministic solutions. This will help us to determine effective deterministic yield equivalents. We present a case example to illustrate the methodology.

In several countries, due to the increasing cost and shortage of water, textile finishing industries are looking for non conventional water resources. The use of reclaimed wastewater appears a technically feasible solution and is gaining a growing consensus. A European Union research project (TOWEF0, Towards effluent zero) with the aim of elaborating a multicriteria integrated and coherent methodology to support the implementation of sustainable water reuse in textile finishing processes has been recently concluded. In order to achieve an optimal compromise between minimization of environmental impacts of the production processes and maximum recovery of resources, Life Cycle Assessment (LCA) methodology has been applied to selected textile products manufactured within Belgian and Italian textile finishing companies. The study identified the key environmental issues within the finishing processes of a variety of natural (cotton, silk) and man-made (polyester, acetate, viscose) fibers and fabrics and analyzed alternative water reuse scenarios. Significant margins exist for impressive reductions in water consumption with almost no additional environmental impact adopting in situ membrane filtration technology. In this paper the methodological approach and the results of the LCA analyses applied to a flax-polyester product are presented and discussed.

"eLCA" is a European Commission financed project aimed at realising “On line green tools and services for Small and Medium-sized Enterprises (SMEs)”. Knowledge and use of Life Cycle Assessment (LCA) by SMEs are strategic to introduce the Integrated Product Policy (IPP) in Europe, but methodology simplification is needed. LCA requires a large amount of validated general and sector specific data. Since their availability and cost can be insuperable barriers for SMEs, pre-elaborated data/meta-data, use of standards and low cost solutions are required. Within the framework of the eLCA project an LCA software - eVerdEE - based on a simplified methodology and specialised for SMEs has been developed. eVerdEE is a web-based tool with some innovative features. Its main feature is the adaptation of ISO 14040 requirements to offer easy-to-handle functions with solid scientific bases. Complex methodological problems, such as the system boundaries definition, the data quality estimation and documentation, the choice of impact categories, are simplified according to the SMEs’ needs. Predefined "Goal and Scope definition" and "Inventory" forms, a user-friendly and well structured procedure are time and cost-effective. The tool is supported by a database containing pre-elaborated environmental indicators of substances and processes for different impact categories. The impact assessment is calculated automatically by using the user’s input and the database values. The results have different levels of interpretation in order to identify the life cycle critical points and the improvement options. The use of a target plot allows the direct comparison of different design alternatives.

Traditional economic analysis methods for manufacturing decisions include only the clearly identified immediate cost and revenue streams. Environmental issues have generally been seen as costs, in the form of waste material losses, conformance tests and pre-discharge treatments. The components of the waste stream often purchased as raw materials, become liabilities at the "end of the pipe" and their intrinsic material value is seldom recognized. A new mathematical treatment of manufacturing economics is proposed in which the costs of separation are compared with the intrinsic value of the waste materials to show how their recovery can provide an economic advantage to the manufacturer. The model is based on a unique combination of thermodynamic analysis, economic modeling and linear optimization. This paper describes the proposed model, and examines case studies in which the changed decision rules have yielded significant savings while protecting the environment. The premise proposed is that by including the value of the waste materials in the profit objective of the firm and applying the appropriate technological solution, manufacturing processes can become closed systems in which losses approach zero and environmental problems are converted into economic savings.

TESPI (Tool for Environmental Sound Product Innovation) is the prototype of a software tool developed within the framework of the “eLCA” project. The project, (www.elca.enea.it)financed by the European Commission, is realising “On line green tools and services for Small and Medium sized Enterprises (SMEs)”. The implementation by SMEs of environmental product innovation (as fostered by the European Integrated Product Policy, IPP) needs specific adaptation to their economic model, their knowledge of production and management processes and their relationships with innovation and the environment. In particular, quality and costs are the main driving forces of innovation in European SMEs, and well known barriers exist to the adoption of an environmental approach in the product design. Starting from these considerations, the TESPI tool has been developed to support the first steps of product design taking into account both the quality and the environment. Two main issues have been considered: (i) classic Quality Function Deployment (QFD) can hardly be proposed to SMEs; (ii) the environmental aspects of the product life cycle need to be integrated with the quality approach. TESPI is a user friendly web-based tool, has a training approach and applies to modular products. Users are guided through the investigation of the quality aspects of their product (customer’s needs and requirements fulfilment) and the identification of the key environmental aspects in the product’s life cycle. A simplified check list allows analyzing the environmental performance of the product. Help is available for a better understanding of the analysis criteria. As a result, the significant aspects for the redesign of the product are identified.

Design for Environment (DfE) has been defined as the systematic integration of environmental considerations into product and process design. And it has been discovered that material and space can be saved when several functions are integrated into a single product by taking advantage of common components. In this design and development project, a multipurpose thresher was designed based on an integrated concept of design for modularity, disassembly, demanufacturing and remanufacturing. The machine can be used to thresh various types of farm produce such as rice, sorghum, cowpea and rye by changing the concave and the cylinder (threshing drum). The configuration of the machine enables access to most of the component parts without changing the tools needed for disassembly because the same type of fasteners was used. Furthermore, the functional units (the shelling unit, the separation unit and the grading unit) were assembled into modules such that only the faulty part needs to be replaced if necessary. The design was so simplified that the operator can make the changes for different uses without any difficulty. The machine has been successfully tested with a number of these products and it is scheduled for tests with other produce like corn and peanuts. The modularity of the functional unit will facilitate multi-lifecycle use of machine and/or its component parts. The uniformity of the liaisons and simplification of the configuration will reduce both the disassembly times and maintenance cost. By this integration, the material requirements for four different machines are conserved, environmental emissions that would be associated with the manufacture, transportation and disposal of four machines are eliminated while the capital requirements by farmers for machinery are reduced to about a quarter. Consequently the total lifecycle cost is kept minimum while the eco-efficiency is maximized.

In this study, we aim to analyze the effect of substitution policies on the on-hand inventory of finished goods for hybrid manufacturing/remanufacturing systems, where both new and remanufactured versions of a product coexist. We consider the case where the remanufactured products are offered to the market for a fraction of the new product price. Here we propose a model that quantitatively measures the pros and cons of supplying a particular demand for a version of the product with a different version in terms of immediate and average long-run costs and benefits. Then using this model we compare the effectiveness of one way and mutual substitution policies both at boundary and non-boundary inventory states.

Recently work has been done about simulation and analysis of manufacturing operations combined with the communications network it operates with. However no such methodology exists in disassembly line context. In this paper, we attempt to enhance their approach and apply it for a disassembly line. To this end, we look at a disassembly line system as a combination of physical processing (performed by machines) and information processing (performed by computer systems), and formulate a model to analyze the system behavior and to obtain an optimal or near optimal solution that would maximize the system performance by minimizing the risk of down time due to network capacity related problems. A case example is presented to demonstrate the feasibility of the model’s implementation.

Product line selection and pricing are two crucial decisions for the profitability of a manufacturing firm. Remanufacturing, on the other hand, may be a profitable strategy that captures the remaining value in used products. In this paper we develop a mixed-integer nonlinear programming model form the perspective of an original equipment manufacturer (OEM). The objective of the OEM is to select products to manufacture and remanufacture among a set of given alternatives and simultaneously determine their prices so as to maximize its profit. It is assumed that the probability a customer selects a product is proportional to its utility and inversely proportional to its price. The utility of a product is an increasing function of its perceived quality. In our base model, products are discriminated by their unit production costs and utilities. We also analyze a case where remanufacturing is limited by the available quantity of collected remanufacturable products. We show that the resulting problem is decomposed into the pricing and product line selection subproblems. Pricing problem is solved by a variant of the simplex search procedure which can also handle constraints, while complete enumeration and a genetic algorithm are used for the solution of the product line selection problem. A number of experiments are carried out to identify conditions under which it is economically viable for the firm to sell remanufactured products. We also determine the optimal utility and unit production cost values of a remanufactured product, which maximizes the total profit of the OEM.

This research investigates the advantages offered by embedded sensors for cost-effective and environmentally benign product life cycle management for desktop computers. During their use by customers as well as at the end of their lives, Sensor Embedded Computers (SECs) by virtue of sensors embedded in them generate data and information pertaining to the conditions and remaining lives of important components such as hard-drive, motherboard, and power supply unit. A computer monitoring framework is proposed to provide more customer comfort, reduce repair costs and increase the effectiveness of current disassembly practices. The framework consists of SECs, remote monitoring center (RMC), repair/service, disassembly, and disposal centers. The RMC collects dynamic data/information generated by sensors during computer usage as well as static data/information from the original equipment manufacturers (OEMs). The RMC forwards this data/information to the repair/service, disassembly, and disposal centers on need-basis. The knowledge about the condition and remaining life of computer components can be advantageously used for planning repair/service and disassembly operations as well as for building refurbished computers with known expected lives. Simulation model of the framework is built and is evaluated in terms of the following performance measures: average downtime of a computer, average repair/service cost of a computer, average disassembly cost of a computer, and average life cycle cost of a computer. Test results show that embedding sensors in computers provides a definite advantage over conventional computers in terms of the performance measures.

Remanufacturing operations involved with highly uncertain recovery rate of used products, subassemblies and parts that complicate the planning and control of the process. In this paper, we develop a comprehensive procedure that determines the optimal input quantities at each stage of the remanufacturing operations in which recovery rates at each stage of the process are stochastic. We model the remanufacturing system as an open queueing network and use the decomposition principle and expansion methodology to analyze it. Each station in the system is subject to breakdown and has a finite buffer capacity. Repair times, breakdown times and service times follow exponential distributions. Optimization is done on the system’s expected total cost using a dynamic programming (DP) algorithm. A numerical example is presented to show the applicability of the model.

As manufacturing industries become more cognizant of the ecological effects that their firms have on the surrounding environment, their waste streams are increasingly becoming viewed not as materials in need of disposal, but rather as resources that can be reused, recycled, or reprocessed into valuable products. Within the food processing sector there are many examples of value-added use of processing residues, although many of these focus solely on utilization as livestock feed ingredients. In addition to livestock feed, though, many other potential avenues exist for food processing waste streams, including food grade as well as industrial products. Unfortunately, the challenge to food processors is actually conducting the byproduct development work. In fact, no clear delineation exists that describes necessary components for an effective byproduct development program. This paper describes one such strategic methodology that could help fill this void. It consists of identifying, quantifying, characterizing, developing, analyzing, optimizing, and modeling the waste stream of interest. This approach to byproduct development represents an inclusive strategy that can be used to more effectively implement value-added utilization programs. Not only is this methodology applicable to food processing operations, but any industrial or manufacturing firm could benefit from instituting the formal components described here. Thus, this methodology, if implemented by a manufacturer, could hold the potential for increasing the probability of meeting the goals of industrial ecology, namely, that of developing and operating sustainable systems.

There are several stories involving the industries that pledge themselves for the environmentally conscious manufacturing practices. Paradigms for environmentally conscious manufacturing are associated with one of the aspects of environmental quality, protection, resource management, commitment or sustainability. The engineering rules of thumb that can easily be adopted by aspiring companies need identification. The underlying thread that unifies the efforts of environmentally conscious manufacturing companies, in offering the environmentally safe products to the world, is grouped and presented in the paper as paradigms for successful practices. The various ways in which a start up company, that wants to excel in environmentally conscious manufacturing, can position itself based on the paradigms is also discussed in the paper.

The University of Texas at Brownsville and Texas Southmost College (UTB/TSC) partners with The Texas Commission on Environmental Quality (TCEQ) to provide pollution prevention and compliance assistance for U.S. based small to medium sized entities (SME’s) located in the Lower Rio Grande Valley border region of Texas. It is anticipated that this training would evolve into environmental management system certification for these entities. This paper discusses pollution challenges and environmental initiatives between Texas and Mexico to confront these challenges and the ongoing cooperative efforts between UTB and TCEQ to enhance the economic and environmental health of the Lower Rio Grande Valley region.

The driving forces behind product take-back and green manufacturing are well established. The two main product end-of-life options are reuse/remanufacturing and recycling. For either option, all take-back units are treated equally because no information that tracks the conditions of a product during its useful life is available. For example, all expired PCs are treated equally; no distinction can be made about which units still have healthy hard disks. This paper discusses sensor-based monitoring and prognostic methodologies for tracking the condition of products while being used by customers and timely and targeted servicing, smart and selective disassembling and refurbishing of products with known (long) remaining lives. The paper also discusses the added benefits to product manufacturers when the time comes to redesign their products. The real-time field data on service and utilization of products are communicated to manufacturers’ headquarters for further analysis.

Packaging material selection (PMS) problems have always been important to packaging designers and engineers. Not only does the selection of packaging material determine the costs and the environmental impacts of packaging, but also influences packaging physical characteristics and associated manufacturing methods. In order to reduce economic and environmental impacts, one has to take a holistic approach to packaging material selection by considering material effects throughout the packaging life cycle. To evaluate economic costs and environmental impacts both quantitative factors and subjective criteria play an important role in the packaging design. In the present work, fuzzy set theory is used for representing and manipulating the vague and subjective descriptions of packaging performance and design attributes. Further a genetic algorithm based approach is used for addressing the packaging material selection problem through multiple criteria decision-making. The overall approach comprises of two phases. In the first phase, fuzzy set theory is used for the linguistic transformation of performance attributes into numerical values. It results in a decision matrix that contains crisp scores. Also in this phase, a weight is assigned to each sub-criterion to show its importance compared to others. In the second phase, a GA is used to globally search for near-optimal or optimal design solutions. The implementation of the proposed methodology is illustrated through a numerical example.