30,795 research outputs found

    A hierarchical approach to multi-project planning under uncertainty

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    We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper

    A hierarchical approach to multi-project planning under uncertainty.

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    We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper.Choice; Complexity; Framework; Hierarchical models; Management; Manufacturing; Methods; Multi-project organisations; Planning; Project management; Project planning; Uncertainty;

    Solution and quality robust project scheduling: a methodological framework.

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    The vast majority of the research efforts in project scheduling over the past several years has concentrated on the development of exact and suboptimal procedures for the generation of a baseline schedule assuming complete information and a deterministic environment. During execution, however, projects may be the subject of considerable uncertainty, which may lead to numerous schedule disruptions. Predictive-reactive scheduling refers to the process where a baseline schedule is developed prior to the start of the project and updated if necessary during project execution. It is the objective of this paper to review possible procedures for the generation of proactive (robust) schedules, which are as well as possible protected against schedule disruptions, and for the deployment of reactive scheduling procedures that may be used to revise or re-optimize the baseline schedule when unexpected events occur. We also offer a methodological framework that should allow project management to identify the proper scheduling methodology for different project scheduling environments. Finally, we survey the basics of Critical Chain scheduling and indicate in which environments it is useful.Framework; Information; Management; Processes; Project management; Project scheduling; Project scheduling under uncertainty; Stability; Robust scheduling; Quality; Scheduling; Stability; Uncertainty;

    A genetic algorithm approach to designing and modelling of a multi-functional fractal manufacturing layout

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    A dynamic and optimal shop floor design, modelling and implementation is key to achieving successful Fractal Manufacturing System (FrMS). To build adaptive and fault-tolerant fractal layout, attention is paid to issues of shop floor planning, function layout, determination of capacity level, cell composition planning and flow distances of products. A full fledged FrMS. layout is multi-functional and is capable of producing a variety of products with minimal reconfiguration. This paper is part and a progression of an on-going project whereby Genetic Algorithm (GA) is adopted to design and model a flexible and multi-functional FrMS floor layout. GA is used in the project for modeling and simulation. The design implementation is done using MATLAB. The result is a fault tolerant configuration that self-regulates and adapts to unpredictable changes in the manufacturing environment arising from lead time reduction pressure, inventories, product customization and other challenges of a dynamic and volatile operational environment

    The Impact of Powers-of-Two Based Schedule on the Minimization of Inventory Costs in a Multi Product Manufacturing Environment

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    This paper discusses about the scheduling problem of a multi product manufacturing industry. Often there has been a problem of applying optimization algorithms to solve the makespan minimization criterion of a job shop due to its inherent NP-hard nature. It is therefore unrealistic to try obtaining a solution through a commercial solver in polynomial time. In this context, we propose a computationally effective heuristic, which is based on the powers-of-two policy in inventory, for solving the minimum makespan problem of job shop scheduling. The research discussed in the current paper is a real time scheduling problem faced by a large scale and complex turbine manufacturing job shop. It is worth noting that by integrating the material requirements planning (MRP) with the feasible schedule obtained, this policy also proves to be useful in minimizing the inventory costs

    The development of a methodology for the evaluation of installed CAPM system’s effectiveness and efficiency

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    The objective of this work was to design, develop and evaluate an audit for a Computer Aided Production Management (CAPM) system. Such systems, despite their costs of purchase and implementation, find wide application in industry but there is still considerable debate as to their contribution to the overall performance of a company. A variety of possible methodologies were explored. However, it was found that most of the existing analytical techniques tended to focus on a comparison of systems with respect to best practice or to require data that a company was unlikely to have. Best practice is not an absolute measure, nor does it take account of different company types and their individual requirements. A flexible methodology, 'the CAPM Audit', designed to establish the effectiveness and efficiency of any installed CAPM system, has been developed. The audit is a development of the Delphi approach and is designed to establish the contribution of the CAPM system to the company's overall competitive position. In its development, a generic model for any CAPM system was devised to facilitate analysis without reference to any particular technology, management mode, or manufacturing control system. The audit developed (in the form of a workbook) consists of four stages: stage one establishes the context; stage two determines the underlying architecture of the system; stage three quantifies the contribution to the company's competitive position; and stage four identifies the causes of any failure of the CAPM system. The design of the audit is such that: it enables a systematic investigation of the effectiveness and efficiency of an installed CAPM system to be completed; it enables the CAPM system's contribution to the company to be identified; and it also enables any inadequacies to be determined

    Intelligent systems in manufacturing: current developments and future prospects

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    Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS
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