{"id":{"repo_id":"aachen","oai_identifier":"oai:publications.rwth-aachen.de:58770"},"canonical_url":"https://search.dev.ndltd.org/etd/aachen/oai:publications.rwth-aachen.de:58770","repository":{"repo_id":"aachen","name":"RWTH Aachen University","base_url":"https://publications.rwth-aachen.de/oai2d"},"display":{"title":"Interaktive Optimierung des Betriebsmitteleinsatzes in der integrierten Projektplanung und -steuerung","abstract":"With the market conditions becoming tougher and tougher, due to more competition through the implementation of the European market, a greater sensitivity for environmental protection with its ensuing impact on planning conditions, project controlling has become more important than ever. One aim of this paper is developing an integrated system of project controlling, i.e. the integration of time planning, cost planning and capacity planning in one single system. It is based on the algorithms of critical path analysis, providing the basic components for time planning. However, to make such a system practical graphic presentations and control mechanisms are required above all. Besides, additional components for deadline and cost checks at any given time plus actual and target comparisons for the past or planning variants are needed. This paper focuses on optimising the use of production facilities. This very field is the least developed in intermediate data systems technology. One essential reason for this is that the computing procedures used so far take so much time even on large computers that they are hardly used in practice. M. Bartusch's thesis and T. Falck's paper outline a method that finds the shortest project duration/span by variations of scheduling with the number of production facilities given. This method has been adapted to computers of intermediate data systems technology. It is supplemented by an exact method providing the lowest number of production facilities by leveling with the project duration given. In addition a target function has been derived additionally smoothing the operation curve of production facilities by applying special heuristics. Wile dealing with these curves it became manifest that a certain flexibility in determining the curve is more often required rather than a minimum number of production facilities. Heuristics in connection with the assessed target function is able to cope with this demand. Maximum use of production facilities as defined by the users can be traced. Tests have demostrated the high quality of heuristic planning results, often identical with the optimum solution. This paper makes available to modern management a system which now in addition to time scheduling and cost budgeting also deals with capacity planning and optimizing in one integrated system.","abstract_html":"With the market conditions becoming tougher and tougher, due to more competition through the implementation of the European market, a greater sensitivity for environmental protection with its ensuing impact on planning conditions, project controlling has become more important than ever. One aim of this paper is developing an integrated system of project controlling, i.e. the integration of time planning, cost planning and capacity planning in one single system. It is based on the algorithms of critical path analysis, providing the basic components for time planning. However, to make such a system practical graphic presentations and control mechanisms are required above all. Besides, additional components for deadline and cost checks at any given time plus actual and target comparisons for the past or planning variants are needed. This paper focuses on optimising the use of production facilities. This very field is the least developed in intermediate data systems technology. One essential reason for this is that the computing procedures used so far take so much time even on large computers that they are hardly used in practice. M. Bartusch's thesis and T. Falck's paper outline a method that finds the shortest project duration/span by variations of scheduling with the number of production facilities given. This method has been adapted to computers of intermediate data systems technology. It is supplemented by an exact method providing the lowest number of production facilities by leveling with the project duration given. In addition a target function has been derived additionally smoothing the operation curve of production facilities by applying special heuristics. Wile dealing with these curves it became manifest that a certain flexibility in determining the curve is more often required rather than a minimum number of production facilities. Heuristics in connection with the assessed target function is able to cope with this demand. Maximum use of production facilities as defined by the users can be traced. Tests have demostrated the high quality of heuristic planning results, often identical with the optimum solution. 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Falck's paper outline a method that finds the shortest project duration/span by variations of scheduling with the number of production facilities given. This method has been adapted to computers of intermediate data systems technology. It is supplemented by an exact method providing the lowest number of production facilities by leveling with the project duration given. In addition a target function has been derived additionally smoothing the operation curve of production facilities by applying special heuristics. Wile dealing with these curves it became manifest that a certain flexibility in determining the curve is more often required rather than a minimum number of production facilities. Heuristics in connection with the assessed target function is able to cope with this demand. Maximum use of production facilities as defined by the users can be traced. Tests have demostrated the high quality of heuristic planning results, often identical with the optimum solution. 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Falck's paper outline a method that finds the shortest project duration/span by variations of scheduling with the number of production facilities given. This method has been adapted to computers of intermediate data systems technology. It is supplemented by an exact method providing the lowest number of production facilities by leveling with the project duration given. In addition a target function has been derived additionally smoothing the operation curve of production facilities by applying special heuristics. Wile dealing with these curves it became manifest that a certain flexibility in determining the curve is more often required rather than a minimum number of production facilities. Heuristics in connection with the assessed target function is able to cope with this demand. Maximum use of production facilities as defined by the users can be traced. Tests have demostrated the high quality of heuristic planning results, often identical with the optimum solution. 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