Produktionsmanagement
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In saturated markets companies have to produce individualized products at low costs. In order to produce the high-variety of products efficiently and to be able to react effectively to order-variations, the production process structures must be most flexible and sustainable. Therefore adaptability of planning processes within the company and the supply chain is a precondition. Moreover an adaptive, decentralized control is necessary, which ensures a synchronized process by a flexible information network across all sub-processes. High Resolution Supply Chain Management aims at designing the production system according to the needs of the company’s supply chain environment.
To reach this goal a consistent research methodology has been elaborated. Based on the Viable System Model (VSM) developed by Stafford Beer current production systems are analyzed preliminary in terms of integrity.
With the gained knowledge a complete recursive model of a Viable Production System is developed. The recursive character of the approach allows identifying independent units within production systems on a detailed level. These units are meant to be self-optimizing control units, whereas the purpose of a unit is to independently optimize its part of the production system or production planning process. The architecture allows modelling a decentralized production system that meets all requirements of a flexible, adaptable production system. Thereupon, research focuses on the development of process and control loops for each of the identified units.
Each unit requires specific input information to be able to achieve a maximum degree of planning accuracy within its boundaries. For the communication of different units a flexible information flow has to be secured. Consequently an additional hierarchical and consistent set of objectives is necessary. Only consistent superior objectives can secure local optimization which yields to something like an overall optimum.
By integrating all results into a complete model of a Viable Production System, the adaptability of planning processes is reached due to the decentralized control of the different units, the consistent set of objectives and flexible information network.
[Conference paper]High Resolution Supply Chain Management – Enabling adaptable planning processes
(2007)
Increased competition has continuously led to a shift of production locations from high-wage to low-wage countries. To counteract this development the manufacturing of customized goods at the costs of mass production is necessary. This goal can be reached by solving the polylemma of production. High Resolution Supply Chain Management provides an approach to achieve higher planning efficiency and production profitability by increased flexibility and value orientation of inter- and in-company production planning and control systems. High Resolution Supply Chain Management aims for the establishment of information transparency within supply chains which does not exist in today's production networks. This will assure the availability of goods by local, self-optimizing control loops. Prerequisite is the creation of communication interfaces and data standards. By assuring the information flow and defined control loops High Resolution Supply Chain Management leads to an adaptive and self-optimized production system. In the last few years globalization led to a higher stress of competition of producing companies in high-wage countries. Cost advantages in production, like lower wages and social contributions, result in a relocation of production plants from countries as e.g. the United States or Germany to low-wage countries. Besides the lower wages the higher profitability is due to cost-effective mass production through economies of scale. At the same time customers ask for more individualized and lower priced products lined up with the wish of shorter lead times. Thus, companies have to gain the capability to adapt rapidly to customers requests. Short customer response times, high flexibility in production planning and -control (PPC) and manufacturing are necessary. Thereby, one frequently neglected competitive advantage of production locations in high-wage countries is the customer proximity. Industry now realizes this advantage and strengthens its efforts towards individualized production. A competitive advantage for high-wage countries can therefore be gained if individualized products are produced at nearly the costs of mass production. Thus, the resolution of the polylemma of production is underlying condition for saving labor in high-wage countries.
The shop floor is a dynamic environment, where deviations to the production plan frequently occur. While there are many tools to support production planning, production control is left unsupported in handling disruptions. The production controller evaluates the deviations and selects the most suitable countermeasures based on his experience. The transparency should be increased in order to improve the decision quality of the production controller by providing meaningful information during his decision process. In this paper, we propose a framework in which an interactive production control system supports the controller in the identification of and reaction to disturbances on the shop floor. At the same time, the system is being improved and updated by the domain knowledge of the controller. The reference architecture consists of three main parts. The first part is the process mining platform, the second part is the machine learning subsystem that consists of a part for the classification of the disturbances and one part for recommending countermeasures to identified disturbances. The third part is the interactive user interface. Integrating the user’s feedback will enable an adaptation to the constantly changing constraints of production control. As an outlook for a technical realization, the design of the user interface and the way of interaction is presented. For the evaluation of our framework, we will use simulated event data of a sample production line. The implementation and test should result in higher production performance by reducing the downtime of the production and increase in its productivity.
Companies operate in an increasingly volatile environment where different developments like shorter product lifecycles, the demand for customized products and globalization increase the complexity and interconnectivity in supply chains. Current events like Brexit, the COVID-19 pandemic or the blockade of the Suez canal have caused major disruptions in supply chains. This demonstrates that many companies are insufficiently prepared for disruptions. As disruptions in supply chains are expected to occur even more frequently in the future, the need for sufficient preparation increases. Increasing resilience provides one way of dealing with disruptions. Resilience can be understood as the ability of a system to cope with disruptions and to ensure the competitiveness of a company. In particular, it enables the preparation for unexpected disruptions. The level of resilience is thereby significantly influenced by actions initiated prior to a disruption. Although companies recognize the need to increase their resilience, it is not systematically implemented. One major challenge is the multidimensionality and complexity of the resilience construct. To systematically design resilience an understanding of the components of resilience is required. However, a common understanding of constituent parts of resilience is currently lacking. This paper, therefore, proposes a general framework for structuring resilience by decomposing the multidimensional concept into its individual components. The framework contributes to an understanding of the interrelationships between the individual components and identifies resilience principles as target directions for the design of resilience. It thus sets the basis for a qualitative assessment of resilience and enables the analysis of resilience-building measures in terms of their impact on resilience. Moreover, an approach for applying the framework to different contexts is presented and then used to detail the framework for the context of procurement.
Many ERP systems support configurable materials. Due to an ever increasing number of product variants the benefits of this approach are well understood. However, these implementations are not standardized. In this article we propose a new standard interface for the exchange of configuration data. This would lead to further benefits as systems as Advanced Planning systems could better use manufacturing flexibility while web shops as Amazon could easily integrate manufacturers of complex products with much reduced implementation effort.
The digital transformation brings up various new tasks to manage new business application software and integrate them into existing business processes and legacy systems, which are necessary to keep e.g. a production system running. Today, all these tasks are on the one hand not clearly defined and on the other hand, responsibility of these cross-disciplinary tasks is unclear in companies being mostly structured in a function-oriented way. While quality management has developed to a firmly established function of process excellence years ago, IT-application management is still to become an inevitable part of the digital transformation. There are just a few authors trying to define and describe this part, the related tasks, and necessary roles in an organization. In this paper, we show how the business needs of a company can influence the ideal adaptation of the digitization solutions and thus become the success of the digital transformation. We base the paper on a use case in manufacturing companies. We then describe how companies deal with business application systems today. Based on the framework Aachen Digital Architecture Management we describe how a company can holistically improve the management of business application systems.
Influenced by the high dynamic of the markets the optimization of supply chains gains more importance. However, analyzing different procurement strategies and the influence of various production parameters is difficult to achieve in industrial practice. Therefore, simulations of supply chains are used in order to improve the production process. The objective of this research is to evaluate different procurement strategies in a four-stage supply chain. Besides, this research aims to identify main influencing factors on the supply chain’s performance. The performance of the supply chain is measured by means of back orders (backlog). A scenario analysis of different customer demands and a Design of Experiments analysis enhance the significance of the simulation results.
The COVID-19 pandemic has shown companies that their on-premise infrastructures often reach their limits with a large number of remote accesses. The transition to cloud-based solutions could represent a more efficient alternative. However, many German companies, especially small and medium-sized enterprises (SME), are still hesitant to take this big step of transferring applications to the cloud. For this reason, this paper examines the question of whether existing migration approaches in the analysis phase fit the specific requirements of SMEs. Using a literature review methodology, we first identify and analyze determinant factors for cloud adoption in SMEs. On this basis, we analyze existing methods in the analysis phase for migrations from on-premise software to cloud solutions. We investigate whether these factors are considered in the analysis phase of the approaches and conclude their suitability for SMEs. Of the migration approaches we examined, none included all the factors we identified as relevant to SMEs. Fewer have considered all factors fully and in detail. We present the results of the literature search process in tabular form and conclude this paper with a discussion and synthesis of the literature as well as an outlook on further research fields.
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.
Analysis of the Harmonizing Potential of Order Processing Attributes in Spread Production Systems
(2010)
The paper discusses an approach how to measure the competitive advantage of harmonized order processing data by making use of knowledge about the interdependencies between related benefit dimensions. Corresponding harmonization projects are all projects that strive for common structures in product attributes, classification systems or product structures. The main objective of the underlying research work is the development of a method for the estimation of the benefit potential of harmonized order processing data.