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Designing the changeability of production logistics
Abstract
Changeability of production logistics has become an important key qualification for sustainable success. In order to achieve high changeability, so called change measures have to be prepared, which enable a quick reaction to changed requirements. This article presents a concept, to plan and prepare these change measures on a strategic level.
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In this paper the results of the study "Germany as a Production Location for Industry" are presented, in which the relevant factors for sustainable competitiveness and job security could be identified. Among the factors for competitive manufacturing companies in Germany ranks, an integrated business software, a real-time data processing and the design of changeable production systems.
Regarding the constantly changing boundary conditions for the industrial creation of value, changeable factories must be challenged. Hence, the common factory planning process is enhanced by simulation techniques. Due to the increasing level of detail and complexity during this planning process, simulation models are characterised by an decreasing amount of changeability. In the prevailing work, the term changeability concerning factory planning and simulation is examined in further detail. For a mutual understanding, a cybernetic model of factory planning is developed. On this basis, three strategies for increasing the changeability of simulation models are depicted.
In international business competition the logistic requirements of industrial enterprises are continuously increasing. The
achievement of manufacturing targets associated with performance significantly depends on production planning and control
(PPC) and its configuration. Due to the fact that the configuration is also based on customer requirements and specific business
conditions general best practices do not exist. This article introduces an approach to support a customized designed selection
and consistent parameterization of the PPC methods. The approach is based on Lödding’s PPC model and combines its different
functions in the sense of a cascaded production control.
Investment decisions for manufacturing systems are primarily based on three characteristics: cost of purchase and operation, cycle time in connection with maximum capacity and achievable work piece quality. However, such considerations neglect another important criterion: the flexibility that allows a manufacturing system to adapt to future production requirements and structures. The major barrier in integrating flexibility into the decision-making process is the difficulty to measure and compare it due to upcoming production scenarios that are not ultimately definable. Therefore, this paper presents a methodical concept for the evaluation of manufacturing systems using real options in order to incorporate flexibility in the decision-making process.