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Die Produktentwicklung beeinflusst die Kostenentstehung eines Produkts über den gesamten Lebenszyklus. Daher müssen vielfältige Restriktionen frühzeitig berücksichtigt werden, wie Beanspruchungen an das Produkt oder Restriktionen aus der Instandhaltung und dem Recycling. Die Produktentwicklung beeinflusst auch maßgeblich die Variantenentstehung und legt die Produktvielfalt, die Produktstruktur und die Kosten der Varianten fest. Die Koordination der Aktivitäten in der Produktentwicklung basiert auf einem produktübergreifenden Projektmanagement, um die interdisziplinäre Zusammenarbeit zu organisieren. [https://link.springer.com/chapter/10.1007/978-3-662-55426-5_23]
This research area focuses on the management systems and principles of a production system. It aims at controlling the complex interplay of heterogeneous processes in a highly dynamic environment, with special focus on individualized products in high-wage countries. The project addresses the comprehensive application of self-optimizing principles on all levels of the value chain. This implies the integration of self-optimizing control loops on cell level, with those addressing the production planning and control as well as supply chain and quality management aspects. A specific focus is on the consideration of human decisions during the production process. To establish socio-technical control loops, it is necessary to understand how human decisions are made in diffuse working processes as well as how cognitive and affective abilities form the human factor within production processes.
Production in high-wage countries can be made more efficient, cost-effective, and flexible by solving the conflict between planning and value orientation. A promising approach is to focus on planning and decision-making processes (production planning and control, design of production processes and machinery, etc.) and to aim to maximize overall planning efficiency. Planning efficiency can be expressed as the ratio between the benefit generated by preparing detailed process instructions to produce the parts or components and the corresponding planning efforts. Industrial companies wanting to gain a competitive advantage in dynamic global markets have to identify a set of non-dominated solutions with the most favorable effort–benefit ratio rather than a single solution. The optimum between detailed planning and the immediate implementation of value-adding activities (process steps) in the process chain needs to be found dynamically for each product.
Working capital management is one of the key disciplines that must be prudently monitored for a firm in pursuit of profits, liquidity and growth. The focus of this paper is on the engineer-to-order manufacturers, and the objective is to analyze the correlations between the reference processes of the engineer-to-order production approach with the key postulates of working-capital management and deliver a mathematical operating curves model, whose purpose and goal is basing on the rationale, that is underlying in the parent logistic operating curves theory. [https://link.springer.com/chapter/10.1007/978-3-319-66926-7_30]
Nowadays one of the most challenging tasks of producing companies is the growing complexity due to the globalization and digitalization. Especially in high wage countries, the ability to deliver fast and to a fixed date gets more and more important. To achieve this logistic target, it is necessary to optimize the Production Planning and Control (hereinafter PPC). This study investigates the effects of a change of the scheduling parameters on a target system. The focused research questions are: How can the effect of a scheduling parametersvariation on the target system of the PPC can be displayed efficiently? Is it possible to review the effect of the scheduling parameters-variation quantitatively and to derive action options?
In order to introduce load management in the manufacturing industry, some obstacles need to be pointed out. This paper presents a feasible approach on how to implement load management measures in companies.
To this end, load management and energy management are explained and distinguished in a first step. Subsequently, the implementation method is introduced. Therefore, by means of this paper, companies will be enabled to use load management measures and significantly reduce their energy costs. In the second part of the paper, the introduced approach will be applied.
Hence, a use case of a manufacturing company is described. Alongside energy analyses with consumption data, specific measures are presented.
In this paper, an approach towards energy management 4.0 will be presented. Energy management 4.0 is understood as an encompassing energy data based concept for manufacturing companies acting in an flexible energy grid of the future with the final goal of autonomous self-optimization Controlling, supervising and scheduling production and logistic steps based on a reliable communication infrastructure and real time data in accordance to achieve a maximum of profitability with regard to human factor is executed.
Guided by a four maturity levels of the "acatech Industrie 4.0 Maturity Index" developed by the German National Academy of Science and Engineering (acatech) different use cases are presented according to the steps of visibility, transparency, prognostic capacity and self-optimization. The basic idea of energy management 4.0 is described and an outlook of further steps that are needed to be evaluated for an implementation are presented.
The topics Internet of Things and Industry 4.0 increasingly lead to the fact that the customer is increasingly focused on manufacturing companies. He wants to know delivery date of the product, wants to make changes at short notice, get an individualized product and much more. Technologically, these requirements have already been met, but the structures within the company as well as the operational processes are not yet or only partially prepared to cope with the increasing complexity and dynamics of production. This leads to many deviations with which the production controller must deal, whether they are complex or trivial.
In order to counteract the increasing number and frequency of deviation situations which are currently encountered with complex manual interventions, it is necessary to systematically evaluate deviations and then to allocate them a dominant reaction strategy (manual, partially automated, automated) from which a suitable reaction measure can be derived. This relieves the production controller, since assistance systems partially eliminate deviations independently.
As a result, the production controller gets more time to deal with the cause of deviations so that a new occurrence of deviations can be avoided and the number of deviations can be reduced sustainably. The following paper provides a solution for the assessment of deviations. In addition, it includes differentiation logic to allocate one of the three different reaction strategies to the identified deviation.
In order to introduce load management in the manufacturing industry, some obstacles need to be pointed out. This paper presents a feasible approach on how to implement load management measures in companies. To do so, load management and energy management are explained and distinguished in a first step. Subsequently, the implementation method is introduced. Therefore, by using this paper, companies will be enabled to use load management measure and reduce their energy costs significantly.