Modeling, Control and Optimisation of Hybrid Systems in a Manufacturing Setting

This study comprises a body of work that investigates the performance of hybrid manufacturing systems. And we have provided a valuable insight into the development of the optimisation techniques for hybrid manufacturing system. With the primary objective of developing prac-tical mathematical algorithms that balance trade-o? cost between product quality and completion time. For sta-bility criterion, a sliding mode control was deployed

System simulation and modeling of electronics demanufacturing facilities

Over the last decade, pressure on the electronic industry has been increasing as concerns for product take-back, product stewardship and global warming have continued to grow. Various end-of-life management options are being expanded including recycling to recapture values from basic materials through reengineering and recovery of subassemblies and individual components for remanufacturing. While progress has been reported on life cycle assessment (LCA), disassembly planning, design for disassembly, and design for environment (DFE), very little research has been focused on demanufacturing from a systems perspective. The objective of this thesis is to build an interface between the user who knows the demanufacturing operation and a software engine, which performs the simulation, collects detailed operational data, and displays results. This thesis bridges the gap between the requirement of hard core simulation knowledge and demanufacturing terminology to present a computerized software tool. Arena, a commercially available discrete event simulation software, acts as an engine for performing these simulations. The developed software tool for demanufacturing contains objects necessary for facility layout, systematic workflow and simulation of the facility. Each object refers to a specific demanufacturing activity and uses detailed simulation logic behind its design to perform that activity. The user selects and locates these objects to layout the facility for a graphical representation of the demanufacturing operation. Objects provide a user screen to input necessary data for the complete description of the activity and its operational characteristics. By simulating the facility for various scenarios, the demanufacturer can compare different options for improving operations, resource utilization, equipment and layout changes. To examine improvement options from an economic perspective a first-order model of demanufacturing costs has been developed and integrated with the simulation software. An activity based unit cost model is used to identify fixed and variable costs associated with each product demanufactured. A small electronics demanufacturing facility was observed and evaluated to validate the simulation modeling and operational logic. The application illustrates the usefulness of demanufacturing system simulation tool to manage and improve the overall efficiency of facilities for economical operation. In summary, a computer-base tool for simulating demanufacturing facility from a systems perspective has been developed and validated. An activity based cost model has been integrated with the simulation to give demanufacturers the ability to examine the full operational and economic trade-offs associated with the business

A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand

In remanufacturing research, most researchers predominantly emphasised on the recovery of whole product (core) rather than at the component level due to its complexity. In contrast, this paper addresses the challenges to focus on remanufacturing through component recovery, so as to solve production planning problems of hybrid remanufacturing and manufacturing systems. To deal with the uncertainties of quality and quantity of product returns, the processing time of remanufacturing, remanufacturing costs, as well as market demands, a robust optimisation model was developed in this research and a case study was used to evaluate its effectiveness and efficiency. To strengthen this research, a sensitivity analysis of the uncertain parameters and the original equipment manufacturer’s (OEM’s) pricing strategy was also conducted. The research finding shows that the market demand volatility leads to a significant increase in the under fulfilment and a reduction in OEM’s profit. On the other hand, recovery cost reduction, as endogenous cost saving, encourages the OEM to produce more remanufactured products with the increase in market demand. Furthermore, the OEM may risk profit loss if they raise the price of new products, and inversely, they could gain more if the price of remanufactured products is raised

A Stochastic Product Priority Optimization Method for Remanufacturing System Based on Genetic Algorithm

Increasing number of manufacturers are developing remanufacturing facilities to recover end-of-life products for product/component reuse and material recycling while the high uncertainty pattern of returned products complicates the production planning. In this thesis a stochastic production priority optimization method, considering various priority concerns for remanufacturing systems is developed. Priority ranking and matching algorithm is developed to determine the priority rule, using thirteen weighting factors. Queueing models are developed to formulate the objective function, a genetic algorithm is then developed to search optimal solution under different business configurations. Result of this research will provide insights to priority assignment mechanism, which in turn provides support to manufacturers in decision-making in production planning thus improving the performance of remanufacturing systems

Optimal Decision Making for Capacitated Reverse Logistics Networks with Quality Variations

Increasing concerns about the environmental impact of production, product take-back laws and dwindling natural resources have heightened the need to address the impact of disposing end-of-life (EOL) products. To cope this challenge, manufacturers have integrated reverse logistics into their supply chain or chosen to outsource product recovery activities to third party firms. The uncertain quality of returns as well as uncertainty in return flow limit the effectiveness of planning, control and monitoring of reverse logistics networks. In addition, there are different recovery routes for each returned product such as reuse, repair, disassembling, remanufacturing and recycling. To determine the most profitable option for EOL product management, remanufacturers must consider the quality of returns and other limitations such as inventory size, demand and quantity of returns. The work in this dissertation addresses these pertinent aspects using two models that have been motivated by two remanufacturing facilities whereby there are uncertainties in the quality and quantity of return and capacitated inventories. In the first case, a disposition decision making model is developed for a remanufacturing process in which the inventory capacity of recoverable returns is limited and where there\u27s a constant demand to be met, for remanufactured products that meet a minimum quality threshold. It is assumed that the quality of returns is uncertain and remanufacturing cost is dependent on the quality grade. In this model, remanufacturing takes place when there is demand for remanufactured products. Accepted returns that meet the minimum quality threshold undergo the remanufacturing processes, and any unacceptable returns are salvaged. A continuous time Markov chain (CTMC) is presented as the modeling approach. The Matrix-Geometric solution methodology is applied to evaluate several key performance metrics for this system, to result in the optimal disposition policy. The numerical study shows an intricate trade-off between the acceptable quality threshold value and the recoverable product inventory capacity. Particularly, there are periodic system starvation whenever there is a mis-match between these two system metrics. In addition, the sensitivity analysis indicates that changes to the demand rate for remanufactured products necessitates the need to re-evaluate the existing system configuration. In the second case, a general framework is presented for a third party remanufacturer, where the remanufacturer has the alternative of salvaging EOL products and supplying parts to external suppliers, or remanufacture the disassembled parts to \u27as new\u27 conditions. The remanufacturing processes of reusable products and parts is studied in the context of other process variables such as the cost and demand of remanufactured products and parts. The goal of this model is to determine the return quality thresholds for a multi-product, multi-period remanufacturing setting. The problem is formulated as a mixed integer non-linear programming (MINLP) problem, which involves a discretization technique that turns the problem turns into a quadratic mixed integer programming (QMIP) problem. Finally, a numerical analysis using a personal computer (PC) remanufacturing facility data is used to test the extent to which the minimum acceptance quality threshold is dependent on the inventory level capacities of the EOL product management sites, varying operational costs and the upper bound of disposal rate

Integration of mahalanobis-taguchi system and activity based costing in decision making for remanufacturing

Classifying components at the end of life (EOL) into remanufacture, repair or dispose is still a major concern to automotive industries. Prior to this study, no specific approach is reported as a guide line to determine critical crankpins that justifying economical remanufacturing process. Traditional cost accounting (TCA) has been used widely by remanufacturing industries but this is not a good measure of estimating the actual manufacturing costs per unit as compared to activity based costing (ABC). However, the application of ABC method in estimating remanufactured cost is rarely reported. These issues were handled separately without a proper integration to make remanufacturing decision which frequently results into uneconomical operating cost and finally the decision becomes less accurate. The aim of this work is to develop a suitable pattern recognition method for classifying crankshaft into three different EOL groups and subsequently evaluates the critical and non-critical crankpins of the used crankshaft using Mahalanobis-Taguchi System (MTS). A remanufacturability assessment technique was developed using Microsoft Excel spreadsheet on pattern recognition and critical crankpins evaluation, and finally integrates these information into a similar spreadsheet with ABC to make decision whether the crankshaft is to be remanufactured, repaired or disposed. The developed scatter diagram was able to recognize group pattern of EOL crankshaft which later was successfully used to determine critical crankpins required for remanufacturing process. The proposed method can serve as a useful approach to the remanufacturing industries for systematically evaluate and decide EOL components for further processing. Case study on six engine models, the result shows that three engines can be securely remanufactured at above 40% profit margin while another two engines are still viable to remanufacture but with less profit margin. In contrast, only two engines can be securely remanufactured due overcharge when using TCA. This inaccuracy affects significantly the overall remanufacturing activities and revenue of the industry. In conclusion, the proposed integration on pattern recognition, parameter evaluation and costing assists the decision making process to effectively remanufacture EOL automotive components as confirmed by Head of workshop of Motor Teknologi Industri Sdn. Bhd

A Conceptual Framework of Reverse Logistics Impact on Firm Performance

This study aims to examine the reverse logistics factors that impact upon firm performance. We review reverse logistics factors under three research streams: (a) resource-based view of the firm, including: Firm strategy, Operations management, and Customer loyalty (b) relational theory, including: Supply chain efficiency, Supply chain collaboration, and institutional theory, including: Government support and Cultural alignment. We measured firm performance with 5 measures: profitability, cost, innovativeness, perceived competitive advantage, and perceived customer satisfaction. We discuss implications for research, policy and practice

04231 Abstracts Collection -- Scheduling in Computer and Manufacturing Systems

During 31.05.-04.06.04, the Dagstuhl Seminar 04231 "Scheduling in Computer and Manufacturing Systems" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available