An integrated decision-making method for selecting machine tool guideways considering remanufacturability

As one of the most important components of machine tool, guideway has an important driving force to comprehensively improve the remanufacturability of machine tools. To select optimal guideway for machine tool remanufacturing, an integrated multi-criteria decision-making (MCDM) approach that combines improved analytic hierarchy process (AHP) and connection degree-based technique of ranking preferences by similarity to the ideal solution (CD-TOPSIS) method is proposed. The improved AHP is employed to calculate the weights of each criterion and the CD-TOPSIS is adapted to complete the task of sorting; finally, the comprehensive evaluation of the alternatives is carried out. A case study, i.e. eight types of guideways, is illustrated to verify the proposed MCDM method. In addition, comparison with existing methods is performed to validate the effective and reliability for the proposed hybrid approach. Also, sensitivity analysis is provided to evaluate the robustness of the method. The final result shows the method provides reliable decision support for the selection of machine tool guideways for remanufacturing

A decision making tool for remanufacturing operations

Remanufacturing industry is increasingly becoming one of the world's attractive business opportunities due to social, economic, and environmental benefits. However, high level of uncertainties in technology selection, imprecise information on availability of core quantity, and lack of standardization of parameters for holistic determination of cost and benefit in remanufacturing processes are among the challenges of this industry. This research developed a decision making tool that consists of a framework for technology selection, model for acquisition of core quantity, and cost and benefit analysis model. The framework considered eight parameters, which are technology costs, operating costs, disposal costs, technology functions, technology quality, technology flexibility, technology obsolete period, and disposal effects. The framework uses fuzzy logic for approximating information and uncertainties to produce results. The results showed that the technology obsolescence for a period of 5 years before it becomes outdated, with disposal effect of 80% leads to 90o/o environment effects. This justifies that rapid technology obsolescence has negative environmental effects. The research also developed a mathematical model to determine the optimal core quantity with the influence of an advertisement factor in controlling shortage of the core return. The model would help decision makers in envisaging availability of core for new remanufacturing investment; hence, a difficulty in core acquisition can be mitigated. The results indicated that the coefficient of media advertisement is a fundamental factor that influences increase rates of core quantity. The model shows that the advertisement factor can increase 41.50 of core availability, which is a step in reducing the degree of uncertainty for the acquisition of core. Moreover, tlte research developed cost and benefit analysis model using fuzzy logic to benchmark minimum cost based on parameters for the processes. The importance of the model is to determine specific values of parameters for the entire processes. The established parameters showed high risk to under-oroverestimate resources for an investment if they were treated in isolation from each process. The results of the case study showed that the increase of production quantity to 72.l2Yo has an advantage compared with the increase of product price to 59.84% as price increase will decrease profit by 44.80%. The framework is unique as it integrates obsolete and disposal phase to evaluate environmental issues. Besides, the mathematical model with advertisement factor has produced results to influence increase of core quantity and bridge the gap of uncertainty for core. Lastly, the cost and benefit model provided accurate value of a parameter to the entire operations, and helped the step-by-step procedures in determining cost and benefit considering standard parameters set to benchmark each process

Optimise repair strategy selection and repair knowledge sharing to support aero engine design.

Recent growth in aviation industry, large civil jet engines OEMs (Original Equipment Manufacturer) and MROs ((Maintenance, Repair and overhaul)) have emphasised on decreased profits, poor technology selections and maintenance focused design. This has generated service based approach in their selling, offering all customers’ requirements, known as servitisation. The servitisation has increased profits but did not solve the challenges of poor technology selection and design. The difficulties involved within servitisation entails rationalised decision making often with high risk and very limited information. This thesis assesses the most suitable Multi-criteria decision making (MCDM) in concurrence with OEMs and MRO focus groups that recognises the industrial requirements and proposed a novel selection method which is an AHP algorithm based on MCDM in efforts to address business KPIs in aero engine servitisation. This AHP algorithm based MCDM develops an optimised repair process/technology selection framework which is called ORSS (Optimised Repair Selection Strategy). The ORSS applies the business KPIs (Quality Cost Delivery) as a selection criteria combined with the repair engineer's requirements and expert's evaluation of processes/technologies based on a component and its damage-mode to provide the optimised repair process/technology selection that also compliments the components lifecycle repair strategy. A structured knowledge sharing framework has also been developed. This consists of the information that the designers can update to help repair teams to become more effective and efficient in repair and services critical information tasks. These frameworks were validated successfully by experts within the design, repair and service teams at Rolls Royce. These frameworks have shown high levels of improvements in repair process selection and the key knowledge sharing for designs.Engineering and Physical Sciences (EPSRC)PhD in Manufacturin