本科生畢業(yè)設(shè)計(jì)(論文)翻譯_確保物流管理和績(jī)效的一致性-資料下載頁(yè)
2024-10-08 08:59本頁(yè)面
【導(dǎo)讀】行為之間的矛盾的水平。定性的模型是影響他們兩個(gè)之間相互依賴水平的因素。專家認(rèn)識(shí)的得到是來。自關(guān)于物流系統(tǒng)促進(jìn)定性的影響模型的解釋和評(píng)價(jià)的動(dòng)態(tài)行為的建模。一致的物流目標(biāo)能夠定義和明確，導(dǎo)向計(jì)劃和控制行為也能夠辨認(rèn)。閉合管理的效果。生產(chǎn)企業(yè)之間的競(jìng)爭(zhēng)是基于產(chǎn)品功能，產(chǎn)品和服務(wù)舒適性價(jià)格產(chǎn)品質(zhì)量和物流績(jī)效。競(jìng)爭(zhēng)優(yōu)勢(shì)二分之一的起源來自于策略設(shè)計(jì)產(chǎn)品或產(chǎn)品系統(tǒng)獨(dú)立性。為了達(dá)到所需要的性能。性能過剩的根源之一。這些公司必須配備績(jī)效管理方法去支持他們避免這些矛盾。首先提供了一個(gè)大概后果，就是物流戰(zhàn)略管理決策要物流績(jī)效管理操作。這文章提出了一種診斷程序和軟件工具是影響制造公司操作物流績(jī)效的因素。的重要后勤目標(biāo)取決于其產(chǎn)品投放策略，“低延遲交付”或“高送可靠性”和“短的交貨時(shí)間”，分別來自主要目標(biāo)。操縱變量的值又決定因素控制：實(shí)際投入的決。量模型理論也有助于一個(gè)定性的物流相互依賴關(guān)系評(píng)價(jià)。
【正文】 logistic performance diagnosis procedure and tool on their basis. A knowledge base containing the insights gained from modelling and analyzing the logistic interdependencies lies at the core of the diagnostic procedure. On the one hand, this enpasses the underlying structure of the logistic interdependencies. For example, the causeandeffect chains leading from the logistic performance measure throughput time via the corresponding controlled and manipulated variables to determinants such as actual capacity provided or date of capacity provision are represented (see fig. 3). On the other hand, the knowledge base includes the guidelines for logistic performance measurement and other results of the evaluation of the interdependencies. These are represented by logical statements such as: The actual capacity provided is the second most effective determinant to influence the performance measure delivery reliability. In the diagnostic tool, the contents of knowledge base are translated into relational databases. Their development and maintenance is facilitated through the expert interface shown at the bottom of fig. 4. Logistics experts are able to modify the structure of the databases and to enter new information into the database tables. Fig. 4. Structure of the diagnostic software prototype The application of the diagnostic procedure and tool prises three phases: performance appraisal, diagnostic analysis and therapy definition. In the first phase, performance data of the manufacturing pany under consideration are collected. This is facilitated through the input section of the user interface of the diagnostic tool shown at the top of fig. 4. An interactive questionnaire provides a structure for the required information on the logistic performance. The logistic configuration, target and actual performance values as well as the logistic planning and control practices applied are recorded. At this stage, logistic performance deficits bee apparent. In the second phase, the performance data are analysed using the databases of the diagnostic software tool. A diagnostic routine systematically determines the causes of logistic performance deficits. The routine identifies inconsistencies between logistic objectives as well as inconsistencies between logistic performance measures and logistic planning and control actions. The diagnosis also points out instances, in which the planning and control practices applied do not maximise logistic performance. In the third phase, therapy rules contained in the database are utilised to ensure the consistency of logistics management practices by defining actions for improvement of the current logistic performance. The causes of logistic performance deficits and the remendations of actions for improvement are highlighted by reports which can by accessed through the user interface (see top of fig. 4). 5 Conclusions The qualitative logistic influence models presented in this paper are a practical means to ensure the consistency of logistic performancebased petitive strategies and operational logistic performance management. Most importantly, the models help manufacturing panies identify those operational planning and control actions, with which they can effectively improve specific logistic performance measures. The fact that the models consider interdependencies between logistic processes as well as those within the processes is an added advantage. Thus, consistent strategic and operational logistics management is facilitated across all logistic processes of a manufacturing pany. Transcending the current state of development, two important enhancements of the qualitative influence models are possible. First, the production processes may be disaggregated into binations of fabrication and assembly processes with variable numbers of production stages and shifting customerorder decoupling points [6, 11]. The development and analysis of the qualitative models should be extended to the resulting more detailed logistic configurations of manufacturing panies. Second, the qualitative models may serve as a basis for the development of additional quantitative logistic models. For example, it is feasible to extend the Theory of Logistic Operating Curves by establishing and verifying the mathematical relationships between the operational planning and control parameters and the logistic performance measures. References
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