Simulation

Many companies are challenged to consider in the planning process for working times not only current laws, labour contracts and their operative goals but also the time-related wishes of their employees. One can identify different types of employees which differ in their working time preferences as well as in the work load they have to deal with in their private lifes. Therefore, the working time configuration has to take the specific situation of the employees into account. Consequently, the process of the working time configuration becomes highly complex. But there are currently no tools available that allow decision-makers of a company to evaluate an intended working time model prospectively (i.e. before its realization) while taking dynamic aspects of their operations as well as the work-life balance of the employees into account. At best, the work-life balance of the employees is a key figure for the evaluation of a working time model but not a parameter during the planning ...

In the field of micro manufacturing, a highly precise adjustment of relevant process parameters is of major importance. The continuing miniaturization of work pieces and machines leads to very small tolerances. The occurrence of so called size-effects interferes with a direct application of knowledge and experiences from macro manufacturing. Moreover, the high specialization of manufacturing technologies and processes in micro manufacturing requires a careful review of each process’s suitability with respect to the involved materials and components. This article presents a method that supports process designers with structured procedures and notations, to model and evaluate technological as well as logistic dependencies along the process chain. Thereby, it supports the selection and configuration of suitable processes for a given process chain.

The fourth industrial revolution promises a further automation of process control by cyber-physical systems. The individual products gain the ability for controlling their production and logistics themselves. By coordinating themselves they can jointly achieve business objectives. This logical decomposition reduces the complexity of cross-company process control significantly. Thus, even exceptions on short notice can be dealt with in real-time. In operation, the required artificial intelligence will usually not be implemented on the active objects. Instead, adequate software platforms for the so-called Industry 4.0 are required. This article investigates the requirements for such platforms and describes how they can be implemented.

Globalization and the growing number of supply chain participants lead to increasing cargo transport service and, thus, to higher energy demand. Although energy prices increase at the same time, the energy balance of production networks remains unconsidered during in the network design phase. Hence, the research project E²Log analyzes how logistics networks and production environment can be coordinated in order to improve energy efficiency. In the first project phase, based on the supply chain for the production of the Volkswagen Amarok, the use case partners have derived simulation scenarios and enhanced a simulation tool to evaluate measures for the efficiency increase without ignoring classic logistic objectives soon.

Global production networks connect partners with outstanding expertise, and make use of regional cost advantages for purchasing and production operations. This development leads to an increasing structural complexity of the networks, which is accompanied by a closer collaboration of dynamic logistics processes. Hence, the resulting dynamics of a large-scale production network is characterized by the dynamics of the individual logistics processes, the dynamics of the network structure and dynamics of the external processes that affect the production network. However, in practice a lack of adequate procedures for the analysis and design of these networks can be observed. The presented article addresses this need by introducing tools and methods for the approximation of large-scale production networks, analysis of their dynamics and the robust design of the network resources.

Planning, design and continuous improvement of today’s complex corporate structures and technical systems require a sophisticated level of extensive know-ledge of technology, processes and IT. To apply planning and simulation tools effectively and efficiently engineers and plant operators have to rise to the challenge to use their knowledge in a goal-oriented way and to expand it within creative processes. Consequently, knowledge is more than ever a key productivity factor and an important component of corporate capital. Against this background, the article discusses possibilities for systematization and standardization in simulation studies and especially approaches to increase productivity in simulation studies by supplying assistance functions as well as systematic evaluation methodologies.

Handling complexity is one of the key topics of producing enterprises worldwide. It can be noted that enterprises are indeed able to coop with the complexity of single processes due to a function-oriented organisation, yet the same organisational paradigm leads to local objective systems that in many cases are contrary to the global goals of the enterprise. The same problem is reflected and supported by the enterprise’s IT systems. Thus, in this paper we present an approach to convert the inflexible function oriented operations into comprehensive processes by introducing special IT systems, so-called logistic assistance systems. To illustrate the approach we introduce the problem of integrated order sequencing and transport planning in the automotive industry and present a prototypical solution.

In view of the demographic changes, questions arise about the long-term development of the performance of work systems with an aging workforce. These questions are especially urgent if work systems with predominantly mental demands should be operated for many years. The simulation tool ESPE-AS can help to forecast the development of the performance of a work system with the given workforce for future periods. This paper describes a first approach of this simulation-based planning method and illustrates it using the routine activities for creating operations plans.

Due to dynamics and complexity within production and delivery networks, customer demands are often highly volatile. In order to achieve a well-founded production planning and control, future customer demands have to be predicted precisely. Classical statistical forecasting methods are often easy to apply but are not able to react on dynamic effects within the data. Methods of nonlinear dynamics consider qualitative in addition to quantitative information within past order data to find possible deterministic structures and, as a result, to achieve better forecasts of the future. This article deals with the development of a data base containing recommendations to choose suitable prediction methods in different situations.

Container terminals are complex logistics systems. In order to achieve highly productive processes and an efficient assignment of the resources, optimization methods and simulation modeling are employed in practice. Based on a case study from the Container-Terminal Altenwerder in Hamburg, this contribution demonstrates how simulation and optimization can be applied to improve the processes related to reefer container handling. We show that optimization methods improve the efficiency of the reefer mechanic operations and how simulation models can support the development and evaluation of such methods in practice.