15,584 research outputs found

    Automatic allocation of safety requirements to components of a software product line

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    Safety critical systems developed as part of a product line must still comply with safety standards. Standards use the concept of Safety Integrity Levels (SILs) to drive the assignment of system safety requirements to components of a system under design. However, for a Software Product Line (SPL), the safety requirements that need to be allocated to a component may vary in different products. Variation in design can indeed change the possible hazards incurred in each product, their causes, and can alter the safety requirements placed on individual components in different SPL products. Establishing common SILs for components of a large scale SPL by considering all possible usage scenarios, is desirable for economies of scale, but it also poses challenges to the safety engineering process. In this paper, we propose a method for automatic allocation of SILs to components of a product line. The approach is applied to a Hybrid Braking System SPL design

    A Novel Optimization towards Higher Reliability in Predictive Modelling towards Code Reusability

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    Although, the area of software engineering has made a remarkable progress in last decade but there is less attention towards the concept of code reusability in this regards.Code reusability is a subset of Software Reusability which is one of the signature topics in software engineering. We review the existing system to find that there is no progress or availability of standard research approach toward code reusability being introduced in last decade. Hence, this paper introduced a predictive framework that is used for optimizing the performance of code reusability. For this purpose, we introduce a case study of near real-time challenge and involved it in our modelling. We apply neural network and Damped-Least square algorithm to perform optimization with a sole target to compute and ensure highest possible reliability. The study outcome of our model exhibits higher reliability and better computational response time

    Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

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    Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

    Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

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    This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADeℱ (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis

    Sustainable Industrial Engineering along Product-Service Life Cycle/Supply Chain

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    Sustainable industrial engineering addresses the sustainability issue from economic, environmental, and social points of view. Its application fields are the whole value chain and lifecycle of products/services, from the development to the end-of-life stages. This book aims to address many of the challenges faced by industrial organizations and supply chains to become more sustainable through reinventing their processes and practices, by continuously incorporating sustainability guidelines and practices in their decisions, such as circular economy, collaboration with suppliers and customers, using information technologies and systems, tracking their products’ life-cycle, using optimization methods to reduce resource use, and to apply new management paradigms to help mitigate many of the wastes that exist across organizations and supply chains. This book will be of interest to the fast-growing body of academics studying and researching sustainability, as well as to industry managers involved in sustainability management

    A Fuzzy Inference System Approach for Evaluating the Feasibility of Product Remanufacture

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    In the recent past, efforts have been made in enhancing sustainable manufacturing aimed at protecting the environment and saving natural resources. Among the efforts that have been explored include strategies to ensure responsible end-of-life product management so as reduce the impact on the environment and achieve effective use of resources. Towards this end, reduce, reuse and recycle product disposal strategies have found a lot of consideration in manufacturing. Of the product reuse strategies, remanufacturing has been widely applied owing to its unique feature of rendering the remanufactured product as good as new. For remanufacturers, this strategy leads to provision of quality products comparable to new their new counterparts at a reduced cost. Remanufacturing also leads to a sustainable environment through energy and material savings, as well as minimized solid wastes. Remanufacturing however, poses challenges related to collection of the returns or cores, manufacturing process planning, resource allocation, warranty estimation and redistribution. These challenges are due to product and process complexities, customer requirements, and uncertainties associated with product take back and the remanufactured products’ market-base. Key among these challenges is the remanufacturing process which is complicated, labor intensive with varying process times. In most cases the routing of these processes is stochastic in nature, based on the condition of the returned product. There is also the negative perception among consumers that remanufactured products are less superior to new ones, which calls for the need to allocate preferably longer warranty periods for the remanufactured product to induce confidence in the consumer while at the same time keeping the warranty costs low. The objectives of this study were informed by challenges faced by a local remanufacturing firm. They include: (1) a detailed study of the current remanufacturing process of the firm’s products; (2) identification of bottlenecks in the process to make recommendations for improvement; (3) develop a decision support system for assessing product remanufacture; (4) assess warranty allocation options for remanufactured product reuse. The study revealed that there are bottlenecks in the current remanufacturing process and suggested an improvement to enhance efficiency. This bottlenecks include overutilization of some of the process centers such as the diagnostic testing and the after-repair testing centers which lead to the product spending more time in the system than necessary. To improve the system performance the capacities of the bottleneck centers were increased which yielded significant reduction in the time the product spends in the system. The key contribution of this dissertation is the development of a decision support system based on a bi-level fuzzy linguistic computing approach. This model integrates qualitative and quantitative product attributes in determining the remanufacturability of a product. The fuzzy-based model established remanufacturability metric, herein referred to as an index, is applied to assess the feasibility of remanufacturing two products that were used as a case study. A number of warranty scenarios are considered to ascertain the impact of different warranty periods on the cost of warranty. The results show that the additional warranty cost for product reuse is a function of the period of first use and the residual life of the produc

    Profit-driven planning and analysis of a WEEE recycling facility with a multi-period MILP model

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    Electronic waste is one of the fastest-growing waste streams in the world. The challenges associated with the recycling of Waste Electrical and Electronic Equipment (WEEE) represent both threats, as the improper disposal of this waste can harm the environment and human health, and opportunities, as this category of waste contains valuable and rare resources that can be recovered and repurposed, contributing to the circular economy. The EU is leading the way in improving the collection and treatment of WEEE, but this has not been sufficient to meet the targets set in its WEEE directive. Therefore, additional efforts must be made to ensure the costeffective and environmentally sound recycling of WEEE, both in the public and private sectors. In this thesis, we propose a multi-period MILP model for the planning of a WEEE recycling facility in Belgium and conduct various analyses to provide insights on what elements are the most crucial to the profitability of such a facility. The originality of our approach lies in the multi-period aspect of the model, and the addition of a limited amount of labour to be allocated to various labour-intensive tasks of WEEE recycling. Our main findings are that labour is the most critical resource, both in cost and utilization, such that the optimal quantity of WEEE to process is the one that results in complete utilization of labour, with little to no overtime. As such, the flexibility of labour, both in possible task allocation and overtime capabilities, is crucial to the proper functioning of the facility, especially when taking into account possible deviations from the optimal plan, caused by the heterogeneity of WEEE and other variations such as the timing of deliveries.nhhma

    An interactive product development model in remanufacturing environment: a chaos-based artificial bee colony approach

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    This research presents an interactive product development model in re-manufacturing environment. The product development model defined a quantitative value model considering product design and development tasks and their value attributes responsible to describe functions of the product. At the last stage of the product development process, re-manufacturing feasibility of used components is incorporated. The consummate feature of this consideration lies in considering variability in cost, weight, and size of the constituted components depending on its types and physical states. Further, this research focuses on reverse logistics paradigm to drive environmental management and economic concerns of the manufacturing industry after the product launching and selling in the market. Moreover, the model is extended by integrating it with RFID technology. This RFID embedded model is aimed at analyzing the economical impact on the account of having advantage of a real time system with reduced inventory shrinkage, reduced processing time, reduced labor cost, process accuracy, and other directly measurable benefits. Consideration the computational complexity involved in product development process reverse logistics, this research proposes; Self-Guided Algorithms & Control (S-CAG) approach for the product development model, and Chaos-based Interactive Artificial Bee Colony (CI-ABC) approach for re-manufacturing model. Illustrative Examples has been presented to test the efficacy of the models. Numerical results from using the S-CAG and CI-ABC for optimal performance are presented and analyzed. The results clearly reveal the efficacy of proposed algorithms when applied to the underlying problems. --Abstract, page iv
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