Decision Support System Classification And Its Application In Manufacturing Sector: A Review

The purpose of this paper is to review decision support system application trend in manufacturing sector. Following the introduction of decision support system, the paper has discussed the application of decision support system in manufacturing sector and identifies the trend in term of decision support system types and their application types. In year 2011 until 2015, the most preferred decision support system were developed by using the model application. It also been found that, most of the developed decision support system are used to support evaluation activities in manufacturing operations. This review provides research trend on decision support system for the recent five years (2011 -2015) in the context of decision support system application in manufacturing industry

A practice based learning environment for engineering students: Acquiring competencies for working on advanced manufacturing engineering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis the author describes the design and operation of a learning environment aimed at imparting technical, technological and managerial knowledge, developing understanding of the underlying issues and enhancing team work skills for an advanced technology future. He offers an analysis of learning, education and training and compares group work with individual tasks, presents a major case study and illustrates the features which distinguish the approach from role play, simulation and experiential learning. When staff at Brunel University were faced with the problem of teaching Computer Integrated Manufacturing (CIM) to engineering students on thin sandwich type undergraduate degree programmes the writer suggested the use of an approach he would later describe as 'practice based learning' or 'real life simulation'. The fourth year course in CIM is designed as a double option for the complementary undergraduate courses, Brunel Manufacturing Engineering (BME) and Special Engineering Programmes (SEP). It is an extension of the Manufacturing Design and Practice course in years one to three of the BME course and of the Design strand on SEP, both of which restrict students' work to the use of individual machine tools and stand alone computing facilities. A wide range of teaching methods is used on the CIM course, including lectures by course staff, presentations by experts and, as the major element, a large group project involving all the students on the course, organised in a management matrix, coordinated by the students and supported by the staff acting as experts. The students also undertake assignment work alongside the technical tasks, to focus their thinking and to improve written communication skills. While the course described cannot replace more than a small proportion of the more conventional lecture, laboratory and tutorial teaching on an engineering programme, it provides a setting where students can experiment and learn about their own strengths and weaknesses in a realistic situation and in the context of teamwork. It also offers a space where they can make quite serious mistakes without direct consequences to their careers. The experience of seven years leads the author to believe that advanced manufacturing technologies and the associated management techniques should be taught in a project based environment with clear and real targets and realistic constraints, offering students challenges to which they can only rise through close and creative team work. The management of task execution must be left largely in the students' own hands. A high level of "consultant" type support is essential though, allied to an assessment scheme which promises and ensures fair treatment of the individual. The different parts of the thesis will be relevant to readers depending on their interest and background. Chapter 1 sets the scene and outlines the approach taken. Following this broad outline of the scope of the dissertation the author places Computer Integrated Manufacturing in a wider context in chapter 2, by providing an introduction to the underlying issues of computer integration and human factors. He puts forward a case for new approaches to the education and training of engineers and managers who will be working in Computer Integrated Manufacturing and Advanced Manufacturing Environments in general. Chapter 3 is devoted to the management of projects while chapter 4 is used to question the role of the engineer. Chapters 5 and 6 provide an introduction to theories of knowledge, teaching, learning and motivation. Chapters 7 and 8 are devoted to particular aspects of engineering education, while chapter 9 reviews the approach used at Brunel University. The topical issues of competence and its relevance to engineering education is discussed in chapter 10, leading into chapters 11 and 12 which deal with aspects of the CIM course. Chapters 13 and 14 are devoted to case-studies and particular tools. The key question of assessment of a practice oriented and team based course is addressed in chapter 15, followed by an evaluation of the CIM process and its application to engineering education of a full time nature which is included in chapters 17 and 18.Funding was obtained from The General Electric Company Prize 1993: Manufacturing Systems Engineering

The development of a metallurgical CAPP system for large steel forgings.

The development of CAPP (Computer Aided Process Planning) systems promises improvement to the design efficiency and quality of process plans, whilst maintaining knowledge for future developments. Although considerable progress has been made in Computer Aided Process Planning, most of the systems developed or under development so far are limited to one manufacturing operation and to planning for an individual part design. The systems lack an overall structure for real manufacturing practice. This thesis examines the problems involved in the planning of an extensive manufacturing task involving many different processes including chemical and thermal treatments. On the basis of the evaluation of the manufacturing system in the collaborating company, an intelligent database system has been designed to solve metallurgical process planning problems involved in the manufacture of large steel forgings. In this CAPP database system, two hierarchy control levels involving a number of local planning areas have been adopted to allow the development of process sub-plans as well as supporting engineering data. All the process sub-plans have been integrated into a single system rather than isolated as separate entities within the overall metallurgical process planning system together with quality assurance control and other functions. These sub-plans, however, are planned and modified in the separate planning areas, the development being conducted on facsimile data records. Only when each sub-plan has reached a satisfactory state of development is it issued - made available to the overall system - by transferring the facsimile records into the system data files, the facsimile records then being discarded.Metallurgical process knowledge and rules have been incorporated into the database. These allow the system to assist users to make decisions and achieve final desired process plans. A versional approach has been developed to organise and control the stage by stage evolution of issued process plans within this complex steel forging environment. The use of separate planning areas and local facsimile records allows the modification of sub-plans already issued to be undertaken on a step by step but secure basis. A fully operating authorisation system controlling access to the data and the deletion or modification of records has been achieved. This is essential in a CAPP system of this type in which historical decisions, or approved rules based on historical experience, are presented to the users as the basis to make new decisions.The work has been extended to explore external enhancement of the central database system with an expert system and with specially written C ++ programmes. The system architecture needed to support this link is described, and issues raised by the enhancement that relate to the overall control are then addressed. The final part of the thesis examines the limitations of the method that has been developed and discusses difficulties involved in implementing a CAPP system in a large concern involved in the 'bespoke' manufacture of complex engineering artifacts on a one-off design basis

Ageneric predictive information system for resource planning and optimisation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe purpose of this research work is to demonstrate the feasibility of creating a quick response decision platform for middle management in industry. It utilises the strengths of current, but more importantly creates a leap forward in the theory and practice of Supervisory and Data Acquisition (SCADA) systems and Discrete Event Simulation and Modelling (DESM). The proposed research platform uses real-time data and creates an automatic platform for real-time and predictive system analysis, giving current and ahead of time information on the performance of the system in an efficient manner. Data acquisition as the backend connection of data integration system to the shop floor faces both hardware and software challenges for coping with large scale real-time data collection. Limited scope of SCADA systems does not make them suitable candidates for this. Cost effectiveness, complexity, and efficiency-orientation of proprietary solutions leave space for more challenge. A Flexible Data Input Layer Architecture (FDILA) is proposed to address generic data integration platform so a multitude of data sources can be connected to the data processing unit. The efficiency of the proposed integration architecture lies in decentralising and distributing services between different layers. A novel Sensitivity Analysis (SA) method called EvenTracker is proposed as an effective tool to measure the importance and priority of inputs to the system. The EvenTracker method is introduced to deal with the complexity systems in real-time. The approach takes advantage of event-based definition of data involved in process flow. The underpinning logic behind EvenTracker SA method is capturing the cause-effect relationships between triggers (input variables) and events (output variables) at a specified period of time determined by an expert. The approach does not require estimating data distribution of any kind. Neither the performance model requires execution beyond the real-time. The proposed EvenTracker sensitivity analysis method has the lowest computational complexity compared with other popular sensitivity analysis methods. For proof of concept, a three tier data integration system was designed and developed by using National Instruments’ LabVIEW programming language, Rockwell Automation’s Arena simulation and modelling software, and OPC data communication software. A laboratory-based conveyor system with 29 sensors was installed to simulate a typical shop floor production line. In addition, EvenTracker SA method has been implemented on the data extracted from 28 sensors of one manufacturing line in a real factory. The experiment has resulted 14% of the input variables to be unimportant for evaluation of model outputs. The method proved a time efficiency gain of 52% on the analysis of filtered system when unimportant input variables were not sampled anymore. The EvenTracker SA method compared to Entropy-based SA technique, as the only other method that can be used for real-time purposes, is quicker, more accurate and less computationally burdensome. Additionally, theoretic estimation of computational complexity of SA methods based on both structural complexity and energy-time analysis resulted in favour of the efficiency of the proposed EvenTracker SA method. Both laboratory and factory-based experiments demonstrated flexibility and efficiency of the proposed solution.The Engineering and Physical Sciences Research Council

Environmentally conscious design : an economic life cycle approach

Companies are under increasing pressure to deal with environmental concerns during product design, for it is the design process which primarily decides the environmental impact of a manufactured product over its life. Tools which assist in taking a life cycle view of the product are a necessary support to designers. Prime amongst these tools is Life Cycle Assessment (LCA). However, a major criticism of LCA methodologies is that while they provide advice on environmentally superior product designs, they do not provide guidance on the economic impact. With product take back increasingly likely to become the responsibility of producer companies attention is now being paid to the later phases of a products life, such as maintenance and disposal costs. A new methodology is shown to be required to complement LCA, one which considers the economic implications of environmentally superior designs over the whole product life. It is argued that a major challenge of such a methodology will be how it deals with the uncertainty associated with the future. The research provides a review of product life cycle design methodologies and a critique of existing approaches to uncertainty. A design teams requirements for decision support that deals with product economic life cycle uncertainty is presented and a decision support methodology which meets these requirements is described. The methodology builds upon the theory of life cycle costing. In practice, the methodology integrates a computer based life cycle model with statistical techniques to quantify the contribution of life cycle variables. In bringing these proven but previously separate tools together the method resolves the issue of uncertainty in a novel and acceptable way. Through the use of an in-depth industrial case study, it is shown that the methodology provides practical support to the design team to produce economically superior product life cycle designs

THE SYSTEMIC REDESIGN OF MANUFACTURING SYSTEMS IN SMALL TO MEDIUM SIZED ENTERPRISES

The research problem was to develop a new approach for redesigning manufacturing systems within Small to Medium sized Enterprises (SMEs). Field observation together with literature review showed that methodologies propounded in theory were not being applied in practice. The research presents a new methodology for the systemic redesign of manufacturing systems within SMEs. The methodology consists of a four phase iterative design strategy consisting of Planning, Risk Assessment, Action and Evaluation leading to the next Planning phase. This is given a systemic basis through four perspectives: Structure; People; Process; and Technology; which frame and guide the Planning phase. Prior to this work there was no systemic approach for redesigning manufacturing systems within SMEs. These findings have been validated through the case study method and against criteria that have been identified and developed by the author. The research adopts three complementary research approaches of participant observation, action research and case study research. These are consistent with the research philosophy developed within the research frame. Participant observation is used at the outset to establish the problem domain and application considerations. Action research is used to develop a methodology that functions independent of the researcher. The final validation is carried out using case study research to evaluate the application of the methodology.CR YDOM Magnetics Ltd. and AGS Home Improvements Ltd

Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresCollaborative networked environments emerged with the spread of the internet, contributing to overcome past communication barriers, and identifying interoperability as an essential property to support businesses development. When achieved seamlessly, efficiency is increased in the entire product life cycle support. However, due to the different sources of knowledge, models and semantics, enterprise organisations are experiencing difficulties exchanging critical information, even when they operate in the same business environments. To solve this issue, most of them try to attain interoperability by establishing peer-to-peer mappings with different business partners, or use neutral data and product standards as the core for information sharing, in optimized networks. In current industrial practice, the model mappings that regulate enterprise communications are only defined once, and most of them are hardcoded in the information systems. This solution has been effective and sufficient for static environments, where enterprise and product models are valid for decades. However, more and more enterprise systems are becoming dynamic, adapting and looking forward to meet further requirements; a trend that is causing new interoperability disturbances and efficiency reduction on existing partnerships. Enterprise Interoperability (EI) is a well established area of applied research, studying these problems, and proposing novel approaches and solutions. This PhD work contributes to that research considering enterprises as complex and adaptive systems, swayed to factors that are making interoperability difficult to sustain over time. The analysis of complexity as a neighbouring scientific domain, in which features of interoperability can be identified and evaluated as a benchmark for developing a new foundation of EI, is here proposed. This approach envisages at drawing concepts from complexity science to analyse dynamic enterprise networks and proposes a framework for sustaining systems interoperability, enabling different organisations to evolve at their own pace, answering the upcoming requirements but minimizing the negative impact these changes can have on their business environment