79,417 research outputs found

    Simulation modelling software approaches to manufacturing problems

    Get PDF
    Increased competition in many industries has resulted in a greater emphasis on developing and using advanced manufacturing systems to improve productivity and reduce costs. The complexity and dynamic behaviour of such systems, make simulation modelling one of the most popular methods to facilitate the design and assess operating strategies of these systems. The growing need for the use of simulation is reflected by a growth in the number of simulation languages and data-driven simulators in the software market. This thesis investigates which characteristics typical manufacturing simulators possess, and how the user requirements can be better fulfilled. For the purpose of software evaluation, a case study has been carried out on a real manufacturing system. Several simulation models of an automated system for electrostatic powder coating have been developed using different simulators. In addition to the evaluation of these simulators, a comprehensive evaluation framework has been developed to facilitate selection of simulation software for modelling manufacturing systems. Different hierarchies of evaluation criteria have been established for different software purposes. In particular, the criteria that have to be satisfied for users in education differ from those for users in industry. A survey has also been conducted involving a number of users of software for manufacturing simulation. The purpose of the survey was to investigate users' opinions about simulation software, and the features that they desire to be incorporated in simulation software. A methodology for simulation software selection is also derived. It consists of guidelines related to the actions to be taken and factors to be considered during the evaluation and selection of simulation software. On the basis of all the findings, proposals on how manufacturing simulators can be improved are made, both for use in education and in industry. These software improvements should result in a reduction in the amount of time and effort needed for simulation model development, and therefore make simulation more beneficial

    Development of a new learning methodology for discrete event simulation by reutilising previous software experience

    Get PDF
    New discrete event simulation software available to industry has significantly reduced the modelling efforts of complex manufacturing problems. These tools enable analysts to assess the viability of potential solutions that better conform to previously defined requirements. Thus, analysts must be conversant in new technologies applications to deliver top quality solutions to the enterprises analysed. Traditional approaches of learning a new technology tend to isolate previous knowledge the analyst possesses in similar application fields and concentrate on features and strengths of the particular application under study. A new approach is therefore needed to capitalise on previous experience an analyst might have, enabling reduction of learning a new technological application by minimising the learning curve effort spent learning the technology, and increasing focus on quantitative and qualitative analysis. [Continues.

    Survey on the use of computational optimisation in UK engineering companies

    Get PDF
    The aim of this work is to capture current practices in the use of computational optimisation in UK engineering companies and identify the current challenges and future needs of the companies. To achieve this aim, a survey was conducted from June 2013 to August 2013 with 17 experts and practitioners from power, aerospace and automotive Original Equipment Manufacturers (OEMs), steel manufacturing sector, small- and medium-sized design, manufacturing and consultancy companies, and optimisation software vendors. By focusing on practitioners in industry, this work complements current surveys in optimisation that have mainly focused on published literature. This survey was carried out using a questionnaire administered through face-to-face interviews lasting around 2 h with each participant. The questionnaire covered 5 main topics: (i) state of optimisation in industry, (ii) optimisation problems, (iii) modelling techniques, (iv) optimisation techniques, and (v) challenges faced and future research areas. This survey identified the following challenges that the participant companies are facing in solving optimisation problems: large number of objectives and variables, availability of computing resources, data management and data mining for optimisation workflow, over-constrained problems, too many algorithms with limited help in selection, and cultural issues including training and mindset. The key areas for future research suggested by the participant companies are as follows: handling large number of variables, objectives and constraints particularly when solution robustness is important, reducing the number of iterations and evaluations, helping the users in algorithm selection and business case for optimisation, sharing data between different disciplines for multi-disciplinary optimisation, and supporting the users in model development and post-processing through design space visualisation and data mining

    Internet enabled modelling of extended manufacturing enterprises using the process based techniques

    Get PDF
    The paper presents the preliminary results of an ongoing research project on Internet enabled process-based modelling of extended manufacturing enterprises. It is proposed to apply the Open System Architecture for CIM (CIMOSA) modelling framework alongside with object-oriented Petri Net models of enterprise processes and object-oriented techniques for extended enterprises modelling. The main features of the proposed approach are described and some components discussed. Elementary examples of object-oriented Petri Net implementation and real-time visualisation are presented

    Recent Achievements in Numerical Simulation in Sheet Metal Forming Processes

    Get PDF
    Purpose of this paper: During the recent 10-15 years, Computer Aided Process Planning and Die Design evolved as one of the most important engineering tools in sheet metal forming, particularly in the automotive industry. This emerging role is strongly emphasized by the rapid development of Finite Element Modelling, as well. The purpose of this paper is to give a general overview about the recent achievements in this very important field of sheet metal forming and to introduce some special results in this development activity. Design/methodology/approach: Concerning the CAE activities in sheet metal forming, there are two main approaches: one of them may be regarded as knowledge based process planning, whilst the other as simulation based process planning. The author attempts to integrate these two separate developments in knowledge and simulation based approach by linking commercial CAD and FEM systems. Findings: Applying the above approach a more powerful and efficient process planning and die design solution can be achieved radically reducing the time and cost of product development cycle and improving product quality. Research limitations: Due to the different modelling approaches in CAD and FEM systems, the biggest challenge is to enhance the robustness of data exchange capabilities between various systems to provide an even more streamlined information flow. Practical implications: The proposed integrated solutions have great practical importance to improve the global competitiveness of sheet metal forming in the very important segment of industry. Originality/value: The concept described in this paper may have specific value both for process planning and die design engineers
    • …
    corecore