Processing of Undesirable Business Events in Advanced Production Planning Systems

Abstract

The paper proposes a novel predictive-reactive planning and scheduling framework in which both approaches are combined to complement each other in a reasonably balanced way. Neither original scheduling algorithms nor original techniques can be find in this paper. It also does not intend to invent new mechanisms or to propose some cardinally new ideas. The aim is to choose, adapt and test ideas, mechanisms and algorithms already proposed by other researchers. The focus of this research is set on make-to-order production environments. The proposed approach aims not only to absorb disruptions in shop floor level schedules but also to mitigate the impacts of potential exceptions, which disrupt mid-term level production plans. It is based on application of risk mitigation techniques and combines various simulation techniques extended by optimization procedures. The proposed approach is indented to be implemented in Advanced Planning and Scheduling system, which is an add-on for Enterprise Resources Planning system. To make it easier to understand the focus of the paper, at the beginning the position from which we start is clarified.

Information Security Risk Assessment in Critical Infrastructure: A Hybrid MCDM Approach

“…Also, it is necessary to determine whether the handling is required for identified risks. If there are risks at the output that need modification to an acceptable level, then the handling phase of risks (mitigation) occurs (Caplinskas et al, 2012). It is possible that risk-handling will not immediately yield the result in an acceptable level of residual risk.…”

Energy efficiency, robustness, and makespan optimality in job-shop scheduling problems

“…The value maxdur represents the maximum duration of a task for the corresponding instance and the expression rand represents a random value between both expressions. Similar expressions were developed to calculate the energy consumption (5,6,7).…”

“…Some recent works have focused on minimizing the energy consumption in scheduling problems (Mouzon & Yildirim, 2008; Dai et al, 2013), mainly from the operations research community (Mouzon et al, 2007; Bruzzone et al, 2012). Furthermore, some works have been carried out to obtain robust schedules to absorb incidences in dynamic scheduling (Caplinkas et al, 2012). However, no works have related energy efficiency with robustness, although there exists a clear relationship between them in job-shop scheduling.…”

Energy Efficiency, Robustness, and Makespan Optimality in Job-Shop Scheduling Problems

“…Recently some works have focused on minimizing the energy consumption in scheduling problems [19] [8], mainly from the Operations Research Community [5], [20]. Furthermore some works have been carried out to obtain robust schedules to absorb incidences in dynamic scheduling [6]. However, no works have related energy-efficiency with robustness although there exist a clear relationship between them in job-shop scheduling.…”