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There is a rich body of literature on sequencing assembly and on sequencing disassembly, but little that either fuses or contrasts the two, which may be valuable for long-range planning in the closed-loop supply chain and simply convenient in terms of consistency in nomenclature and mathematical formulations. The purpose of this paper is to concisely unify and summarize assembly and disassembly formulae – as well as to add new formulations for completeness – and then demonstrate the similarities and differences between assembly and disassembly.

Along with several familiar assembly-line formulae which are adapted here for disassembly, five (two specific and three general) metrics and a comparative performance formula from disassembly-line balancing are proposed for use in assembly- and disassembly-line sequencing and balancing either directly, through generalization, or with some extension. The size of assembly and disassembly search spaces are also quantified and formulated. Three new metrics are then developed from each of the general metrics to demonstrate the process of using these general formulae as prototypes.

The three new metrics along with several of the original metrics are selectively applied to a simple, notional case study product to be sequenced on an assembly line and then on a disassembly line. Using these analytical results, the inherent differences between assembly and disassembly, even for a seemingly trivial product, are illustrated.

The research adds several new assembly/disassembly metrics, a case study, unifies the evaluation formulae that assembly and disassembly hold in common as well as structuring prototype formulae for flexibility in generating new evaluation criteria for both, and quantifies (using the case study) how assembly and disassembly – while certainly possessing similarities – also demonstrate measurable differences that can be expected to affect product design, planning, production, and end-of-life processing.

The purpose of this paper is to introduce sequence‐dependent disassembly line balancing problem (SDDLBP) to the literature and propose an efficient metaheuristic solution methodology to this NP‐complete problem.

This manuscript utilizes a well‐proven metaheuristics solution methodology, namely, ant colony optimization, to address the problem.

Since SDDLBP is NP‐complete, finding an optimal balance becomes computationally prohibitive due to exponential growth of the solution space with the increase in the number of parts. The proposed methodology is very fast, generates (near) optimal solutions, preserves precedence requirements and is easy to implement.

Since development of cost effective and profitable disassembly systems is an important issue in end‐of‐life product treatment, every step towards improving disassembly line balancing brings us closer to cost savings and compelling practicality.

This paper introduces a new problem (SDDLBP) and an efficient solution to the literature.

Although disassembly balancing lines has been studied for over two decades, there is a gap in the robotic disassembly. Moreover, combination of problem with heterogeneous employee assignment is also lacking. The hazard related with the tasks performed on disassembly lines on workers can be reduced by the use of robots or collaborative robots (cobots) instead of workers. This situation causes an increase in costs. The purpose of the study is to propose a novel version of the problem and to solve this bi-objective (minimizing cost and minimizing hazard simultaneously) problem.

The epsilon constraint method was used to solve the bi-objective model. Entropy-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization methods for Enrichment Evaluation (PROMETHEE) methods were used to support the decision-maker. In addition, a new criterion called automation rate was proposed. The effects of factors were investigated with full factor experiment design.

The effects of all factors were found statistically significant on the solution time. The combined effect of the number of tasks and number of workers was also found to be statistically significant.

In this study, for the first time in the literature, a disassembly line balancing and employee assignment model was proposed in the presence of heterogeneous workers, robots and cobots to simultaneously minimize the hazard to the worker and cost.

The purpose of this paper is to efficiently solve disassembly line balancing problem (DLBP) and the sequence-dependent disassembly line balancing problem (SDDLBP) which are both known to be NP-complete.

This manuscript utilizes a well-proven metaheuristics solution methodology, namely, variable neighborhood search (VNS), to address the problem.

DLBPs are analyzed using the numerical instances from the literature to show the efficiency of the proposed approach. The proposed algorithm showed superior performance compared to other techniques provided in the literature in terms of robustness to reach better solutions.

Since disassembly is the most critical step in end-of-life product treatment, every step toward improving disassembly line balancing brings us closer to cost savings and compelling practicality.

This paper is the first adaptation of VNS algorithm for solving DLBP and SDDLBP.

Reverse supply chain (RSC) is an extension of the traditional supply chain (TSC) motivated by environmental requirements and economic incentives. TSC management deals with planning, executing, monitoring, and controlling a collection of organizations, activities, resources, people, technology, and information as the materials and products move from manufacturers to the consumers. Except for a short warranty period, TSC excludes most of the responsibilities toward the product beyond the point of sale. However, because of growing environmental awareness and regulations (e.g. product stewardship statute), TSC alone is no longer an adequate industrial practice. New regulations and public awareness have forced manufacturers to take responsibilities of products when they reach their end of lives. This has necessitated the creation of an infrastructure, known as RSC, which includes collection, transportation, and management of end-of-life products (EOLPs). The advantages of implementing RSC include the reduction in the use of virgin resources, the decrease in the materials sent to landfills and the cost savings stemming from the reuse of EOLPs, disassembled components, and recycled materials. TSC and RSC together represent a closed loop of materials flow. The whole system of organizations, activities, resources, people, technology, and information flowing in this closed loop is known as the closed-loop supply chain (CLSC).

In RSC, the management of EOLPs includes cleaning, disassembly, sorting, inspecting, and recovery or disposal. The recovery could take several forms depending on the condition of EOLPs, namely, product recovery (refurbishing, remanufacturing, repairing), component recovery (cannibalization), and material recovery (recycling). However, neither the quality nor the quantity of returning EOLPs is predictable. This unpredictable nature of RSC is what makes its management challenging and necessitates innovative management science solutions to control it.

In this chapter, we address the order-driven component and product recovery (ODCPR) problem for sensor-embedded products (SEPs) in an RSC. SEPs contain sensors and radio-frequency identification tags implanted in them at the time of their production to monitor their critical components throughout their lives. By facilitating data collection during product usage, these embedded sensors enable one to predict product/component failures and estimate the remaining life of components as the products reach their end of lives. In an ODCPR system, EOLPs are either cannibalized or refurbished. Refurbishment activities are carried out to meet the demand for products and may require reusable components. The purpose of cannibalization is to recover a limited number of reusable components for customers and internal use. Internal component demand stems from the component requirements in the refurbishment operation. It is assumed that the customers have specific remaining-life requirements on components and products. Therefore, the problem is to find the optimal subset and sequence of the EOLPs to cannibalize and refurbish so that (1) the remaining-life-based demands are satisfied while making sure that the necessary reusable components are extracted before attempting to refurbish an EOLP and (2) the total system cost is minimized. We show that the problem could be formulated as an integer nonlinear program. We then develop a hybrid genetic algorithm to solve the problem that is shown to provide excellent results. A numerical example is presented to illustrate the methodology.

In this chapter, a case of reverse supply chain is considered, where a product recovery facility receives sensors and Radio Frequency Identification (RFID) tags embedded End-Of-Life (EOL) products. Sensors and RFID tags can capture and store component’s life cycle information during its economic life. This technology can provide data about contents and conditions of products and components without the need of actual disassembly and inspection. It also determines the remaining lives of the components which eventually translate into their quality levels.

The example considered here presents an advanced-repair-to-order-and-disassembly-to-order system. It disassembles the components to meet the components’ demands, repairs the products to meet the products’ demands and recycles the materials to meet the materials’ demands. The received EOL products may have different design alternatives. The objective of the proposed multi-criteria decision-making model is to determine which of the design alternatives is best in fulfilling the various criteria.

This paper considers CSCMP Supply Chain Hall of Famer Henry Ford's innovation and its transformative impact on supply chain management. Credited with the assembly line, Ford's innovation also included a supply chain design around the concept of flow, integrated supply and the enablement of economies of scale and productivity to drive down consumer prices and create affordable product for a growing market.

This paper considers literature and builds upon the history of the innovation to consider supply chain implications and future opportunities to further the innovation into modern supply chains.

Ford did not “invent” the assembly line but he did build the supply chain around it. He stewarded core supply chain principles of great relevance well before they become popular, including a focus on lifelong learning, making failure safe, waste elimination and helping make the world a better place. There are many opportunities to continue to build upon the innovation for future supply chain success.

The supply chain field is sometimes said to be “historically challenged.” This paper reviews the essence and lessons learned from the assembly line and supply chain design and the leadership principles of Henry Ford and the Ford production system. We also connect leadership principles of the Ford supply chain to those of Ohno and Deming to map out the evolution of the Ford supply chain management approach over multiple decades and into the supply chain body of knowledge. Finally, we reflect upon how supply chain design aspects of the Ford supply chain may need to further evolve into the future. Based upon this reflection we recommend opportunities for further research and innovation that build upon the supply chain management roots provided by Henry Ford.

Disturbing increase in the use of virgin resources to produce new products has threatened the environment. Many countries have reacted to this situation through regulations which aim to eliminate negative impact of products on the environment shaping the concept of environmentally conscious manufacturing and product recovery (ECMPRO). The first crucial and the most time-consuming step of product recovery is disassembly. The best productivity rate is achieved via a disassembly line in an automated disassembly process. In this chapter, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) with multiple objectives that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent time increments among disassembly tasks. Due to the high complexity of the SDDLBP, there is currently no known way to optimally solve even moderately sized instances of the problem. Therefore, an efficient methodology based on the simulated annealing (SA) is proposed to solve the SDDLBP. Case scenarios are considered and comparisons with ant colony optimization (ACO), particle swarm optimization (PSO), river formation dynamics (RFD), and tabu search (TS) approaches are provided to demonstrate the superior functionality of the proposed algorithm.

Combining of natural and synthetic materials in apparel products caused problems with material recovery, reuse, recycling, or composting at the end of product life. The purpose of this paper is to investigate the application of design for disassembly methods in the design and construction of men's jacket. With this type of design, consumers and manufacturers can easily compost, recycle, or reuse different materials and components at the end of the garment's usable life.

After analyzing the men's jackets available in the market and identifying obstacles to disassembly, the authors designed and constructed a man's jacket that can be easily disassembled. The jacket design for disassembly focused on material selection, jacket design, and stitch evaluation and selection. The disassembly time was also measured.

It was found that minimizing material diversity and sewing similar materials together whenever possible, replacing fusible interfacing with blind hemming stitches under the collar and on the backside of the lapel, and using an appropriate low density stitch to sew the wool outer shell and polyester lining together, can make the jacket disassemble easily into a compostable outer shell and recyclable lining within 1.5 min.

This research provided a pilot study demonstration of applying “design for disassembly” in apparel design and construction. The findings could be employed in different apparel products to help reduce environmental pollution and resource depletion problems related to the apparel industry.

The purpose of this paper is to present an interactive system to enable product design for disassembly and to offer robust and quick design solutions based on designers’ input.

The system utilizes an interactive questionnaire to communicate with the designer. The questionnaire is in the form of binary questions (Yes/No) and design questions that would enable the system to learn the objectives of the design. Solutions are based on a CAD supported design platform. The efficiency of each design is calculated using disassembly time as the metric of measurement using motion-time measurement (MTM). The designer would be able to make an informed decision with respect to component functionality, ease of disassembly and disassembly time. The paper presents a detailed framework and structure of this system.

The value of the system is corroborated by means of a case study of an actual product design. The system is structured to offer multiple solutions to a design problem so as to enable the designer to choose the option that best serves their needs.

This novel interactive system would accept customers’ design preferences as input and offer multiple solutions in order to solve the design problem. Process time is directly calculated using the MTM system of measurement by converting design features into time measurement units. Disassembly time can then be easily converted into disassembly cost by using standard conversion rates. The value to designers is obvious.