Christina Thomas

Approach for Reducing Data Inconsistencies in Production Control

Companies of the manufacturing industry gather a high number of different high-resolution data concerning production and manufacturing processes. Advanced Planning and Scheduling Systems use these data sets collected on the shop-floor in order to adjust their scheduling for near- and middle-term production orders. Usually, the quality of these production feedback data is reduced by inconsistencies and errors which impairs the results of the planning process. The consequence is a low adherence to planned delivery dates. In this paper typical data inconsistencies are analysed for their rate of occurrence and an approach for reducing data inconsistencies by applying association rule induction is proposed.

Cyber-Physical Production Management

Today a high adherence to delivery dates is the main logistic target for manufacturing companies. To control the increasing complexity of production planning and control manufacturing companies use IT systems. However, the applied IT systems often do not provide a reliable forecast of delivery dates and thus affect the required adherence to delivery dates. The paper describes a cyber-physical approach to optimize the production planning and control towards a reliable detailed planning. Therefore, it is necessary to determine the deviations between the production schedule of the IT system and the production processes in reality. With the knowledge of the revealed deviations and their causes the process of production planning can be adjusted towards a more dependable high resolution production planning and control.

Self-Optimizing Decision-Making in Production Control

This paper deals with the concept for self-optimizing decision-making in production planning and control. The concept is based on a value stream that provides real-time production data. This data enables a qualified decision regarding production planning and control. Practice has shown that production systems with a high production process complexity—such as job shop production with low volume production—are difficult to control automatically. Therefore, employees have an important role to play but need to be supported regarding their decision-making. The goal is to highlight relevant decisions and put them into the correct context. An unconventional and interactive illustration that abandons classic numerical key performance indicators helps to derive the correct decisions. Varying levels of detail regarding the depicted data allow the user to “zoom” in or out of the state of his production system. By support of simulation and visualization tools, the aim of this paper is to present a concept for self-optimizing decision-making in production control in order to help user making the right decision.

Web-based value stream oriented simulation of production control

Production control faces the challenge to cope with high market dynamics and high complexity in production structures. Therefore, simulation is often used to configure production control properly. Today, the generation and configuration of these simulation models need expert knowledge and cause high costs. The presented approach shows how simulation models can be generated in short times and without expert knowledge within simulation. Therefore a web-based platform is configured, which enables the employees to generate a simulation model of the production. Since the structure of these simulation models is modular, the employees can upload input data and chose different strategies of production control by themselves in order to optimize their current production control. By integration of employees within the simulation generation process, the acceptance in simulation and in simulation results increases.

Designing Rotationally Symmetric Products for Multi-variant Mass Production by Using Production-Technical Solution Space

Highly customized products have led to an irreproducible complexity in product development and order processing process. Today’s product design and IT-tools reduce this complexity insufficiently and potentials in administration and manufacturing are not fully lapped. The approach presented in this paper starts the development of a product structure at the manufacturing environment. The aim is to develop a product structure for rotational products that is adapted for manufacturing processes and therefore enabling a cost-effective production. As a result, companies are able to provide their customers with individual product solutions using standardized processes. This enables a technological and production-related flexibility to fulfill growing needs of global markets.

Analyzing the Effects of Production Control on Logistic Targets with Web-Based Simulation Model

Manufacturing companies are facing the challenge to cope with individualized process chains in spite of high market dynamics. In order to achieve high process efficiency by realizing logistic targets, two main leverages can be identified: adjustment of production structure and configuration of production control. The production structure represents the layout and arrangement of machines, the organization of production processes as well as the information and material flow. Once installed, it is often set for a long period of time and therefore represents the basis for further elements in a production environment such as production control. The dilemma of production planning and control is to achieve high process efficiency, low throughput times and good planning confidence while customers demand short product-lifecycles, an increasing product variety and a growing individualization of products. Within this paper, a simulation-based study about the effects of production structure and production control to logistical targets is introduced.

Quantitative Process Maps - A Concept for Prioritization of Business Process Improvement Projects

Modern large-scale companies are facing the challenge of how to prioritize improvement projects for business processes. This article offers a concept on how to approach this challenge using quantitative process maps. For the process maps treemaps are used, visualizing the most important processes of a company and the degree of needed change. Inside the article, the way to build up the process map, deriving important processes from the strategy and evaluating them regarding risks, maturity level, key performance indicators and given improvement ideas from idea management, is described. The paper also offers a concept for building up responsibilities and structuring the yearly process for process optimization.