decision making

Efficient operation and maintenance (O&M) processes are important success factors to reduce the operating costs in the operation phase of industrial assets. Therefore, companies use different maintenance strategies that are well known from literature. Due to uncertainties in occurrence of faults and the duration of process fulfilment, strategies even supported by new technologies do often not fit to the specific real-world challenges. The focus of this paper is to discuss a new concept where operation data analysis is used to support decisions for logistics maintenance processes.

Challenging managerial decisions are more frequent under unpredictable environmental conditions. After clarification of the term “difficulty” in a decision-making, most important psychological misinterpretations and false evaluations are explained and the phenomenon of risk diffusion and cognitive control are discussed.

Due to shortening product life cycles, complex supplier networks and an increasing number of parties involved, the decision making process has become both more critical and more difficult. The complexity and dynamics of the ramp-up phase make it necessary to not try to concentrate the decisions in on hand, but rather distribute decisions among decentralized yet competent decision makers on-site. It is, however, necessary to provide the decentralized decision makers with the basis and the capability of decision making, and a joint target system to ensure optimal outcome. The paper presents a heuristic approach to design and operate production ramp-up appropriate to stable and efficient ramp-up processes.