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In the previous chapters, I set out a conceptual model of trauma-informed servant leadership and discussed servant leadership supervision for working with burnout, compassion fatigue and secondary trauma in employees within trauma related health and social care settings. In this chapter, I further extend servant leadership to the peer support principle in trauma-informed approaches (Substance Abuse and Mental Health Services Administration, 2014). The first part of this chapter will examine peer support work (PSW) and report on the outcomes associated with it. Then, servant leadership will be discussed and used to operationalise the principle of peer support as set out in trauma-informed approaches. A servant leadership peer support approach is put forward with a theoretical basis. This theoretical model has been slightly changed from the previous servant leadership approaches discussed, in order to represent the PSW role more accurately. However, as discussed previously, it is not the characteristics of the Servant leadership (SL) model that define the approach, rather the philosophy and desire to serve first. In the last section of this chapter, Martha Griffin brings the characteristics of this model to life using her vast experience and discusses some of the potential challenges faced by peers in training and practice.

The purpose of this paper is to propose a framework to identify all the feasible disassembly sequences for a multi‐component product and to find an optimal disassembly sequence, according to specific criteria such as cost, duration, profit, etc.

Taking into account topological and geometrical constraints of a product structure, an AND/OR disassembly graph is built. Each graph node represents a feasible subassembly. Two nodes i and j are connected by an arc (i, j), called a transition, if the subassembly j can be obtained from the subassembly i by removing one or several connectors. Constraint programming approach is used to generate the feasible subassemblies and related transitions.

If a cost z_ij is incurred to perform a transition (i, j), an optimal disassembly sequence can be generated for a given subassembly, using the shortest path algorithm or a linear programming model.

The proposed approach performs very well compared to other approaches published in the literature, even when applied to products requiring parallel disassembly and including a large number of parts.

This approach has been successfully applied to assess the wheelchair maintainability at the design stage and will be implemented in CAD systems. One other application, regarding the disassembly process and total revenue maximization for product recycling, is now under consideration.

Applying constraint programming to efficiently generate the set of the feasible subassemblies constitutes the main contribution in this paper. This process is the hardest step in the disassembly sequencing problem.

In this paper, we consider the disassembly-to-order (DTO) problem, where a variety of returned products are disassembled to fulfill the demand for specified numbers of components and materials. The objective is to determine the optimal numbers of returned products to disassemble so as to maximize profit and minimize costs. We model the DTO problem using a multi-criteria decision-making approach. Since the conditions of returned products are unknown, the yields from disassembly are considered to be stochastic. To solve the stochastic problem, we use one of the two heuristic approaches (viz., one-to-one approach or one-to-many approach) that converts the problem into a deterministic equivalent. We compare the performance of the two heuristic approaches using a case example.

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.

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.

Maintenance disassembly that involves separating failed components from an assembly or system plays a vital role in line maintenance of civil aircraft, and it is necessary to have an effective and optimal sequence planning in order to reduce time and cost in maintenance. The purpose of the paper is to develop a more effective disassembly sequence planning method for maintenance of large equipment including civil aircraft systems.

The methodology involves the following steps: a component‐fastener graph is built to describe the equipment in terms of classifying components into two categories that are functional components and fasteners; interference matrix is developed to determine the removable component, and a disassembly sequence planning of functional components is proposed based on Dijkstra's algorithm; the disassembly sequence planning including fasteners is presented based on particle swarm optimization.

An application case, which takes the nose landing gear system of a regional jet as a study object, shows that the disassembly sequence planning method proposed in the paper can reduce the calculation complexity greatly, and its effectiveness is greater than that of a genetic algorithm‐based method, in most situations.

The method proposed herein can acquire the optimal maintenance disassembly sequence, which can reduce the cost and time for maintenance of large equipment.

A novel and effective disassembly sequence planning solution for maintenance of large equipment is presented, which can be applied to the line maintenance of civil aircraft.

Owing to the manufacturing trend of stringent product disposal regulations, a new business scenario, which requires an alternative disposal option on consumer products and further product recovery operations, is increasingly important for promoting sustainable supply chain performance. The purpose of this paper is to explore the use to post‐use stage of the product lifecycle, that may have significant potential for increasing product utilisation value and reducing product disposal to landfills.

The paper proposes a re‐classification of the 6R (reduce, recover, redesign, reuse, recycle, remanufacturing) methodology for rectifying waste minimisation along a supply chain, to increase product utilisation at the post‐use stage.

Intensive study of 6R considerations to improve end‐of‐life planning and strategy and extend of product lifecycle management is lacking. None of the existing supply chain frameworks clearly illustrates the aspects of 6R perspectives for the use to post‐use stage.

The main limitation is that this study only focuses on 6R perspective for achieving waste minimisation along a supply chain. There is a need to explore various practical issues of the implementation, including the establishment of specific performance metrics for various manufacturing industries to assess organisational performance.

This proposed sustainable supply chain for collaborative manufacturing may provide a very useful source of what needs to be implemented and achieved to meet the requirements of sustainability, which is the current and future trend of manufacturing.

This paper provides some of the insights into holistic aspects of 6R perspective to increase product utilisation value between use and post‐use stages.

The purpose of this paper is to enhance the method developed by previous researchers. In addition to using the combined interference matrix, the combined connection matrix and the combined contact matrix of product components, the disassembly sequence matrix and the combined instability matrix with platform to evaluate instability of sub‐assemblies are built, and effects of changes of sub‐assembly disassembly directions or tools and the effect of gravity are considered to obtain the best disassembly sequence for a product with many components. A computer program is generated and results of two cases are compared with those of the available studies.

The methodology includes the combined interference matrix, the combined contact matrix and the combined connection matrix of components for a product. The combined instability matrix of sub‐assemblies, changes of sub‐assembly disassembly direction or tools, and the effect of gravity during operation are considered. The binary number system is used to simplify relations among components of a product.

This methodology enhances the existing method and software is generated. Results of two cases are compared and show the same optimum disassembly processes as those obtained from other researchers.

All matrices are defined by the directions of x, y and z with three axes perpendicular to each other. The computer program generated cannot be used for a product with components that must be disassembled in the directions different from the axes.

Two cases are used to investigate feasibility of the proposed methodology with the computer program generated. The first one is an electric drill, and the second one is a flash lighter.

The methodology described in this paper is feasible for study of disassembly processes of products. The software generated can be used to obtain the optimum disassembly process of products.

The purpose of this paper is to evaluate the service quality automobile garages through development of a service quality index based on the factors influencing service quality.

A structural methodology of graph theory and matrix approach is applied for developing the service quality index.

The automobile maintenance can be considered as a service industry and in order to sustain in the competitive business environment, the service providers must ensure quality in their services. There are several factors that influence the service quality. Each factor is comprised of several sub-factors. Moreover, the factors are interrelated with each other. Modelling of these factors and their interrelations with due consideration of their structure is accomplished through the graph theory. The directed graph (digraph) of the service quality is defined; the nodes of this symbolize the quality influencing factors, while the edges represent their degrees of interrelationships. An equivalent matrix developed from the digraph establishes a service quality function which leads to evaluation of service quality index (SQI). A greater value of the service quality index displays that the organization and functioning of the garage is adequate.

The methodology can be applied for evaluating as well as comparing service quality of different garages. The observations would be helpful to the managers the garages to make strategies for improving their service quality.

The paper establishes the interrelations among various factors that influence the service quality at automobile garages and develop a numeric index for the evaluation of the same.

The purpose of this paper is to propose an approach to evaluate product performance of returned products, using four key performance attributes as the basis for improving sustainability through product recovery.

A fuzzy logic approach is developed to account a trade-off scenario for a manufactured product with recovery options. This approach is demonstrated using a numerical example and is validated using a case study in the automotive parts and components industry.

Product utilisation value (PUV) is found to be a useful index that manufacturers can use to assess product recovery options, as it brings together a number of conflicting parameters into a rationalised value for decision making. In addition, PUV provides a rationalised approach for comparing and selecting the most appropriate recovery configuration option.

The authors only utilise four key performance measures to derive PUV. Further research is needed to modify and incorporate other measures that are important to decision makers to improve sustainability in manufacturing supply chains.

The proposed approach may motivate decision makers to consider sustainable recovery options by comparing PUVs of products for primary and secondary markets. The case study demonstrated the conflict and complexity organisations face in a global supply chain of a competitive industry.

The authors propose an approach to optimise trade-off considerations of selected performance attributes through PUV. This PUV as a benchmark can help improve recovery of the returned products and reduce landfill.