Conceptual approach for integrating condition monitoring information and spare parts forecasting methods

Abstract

Precise estimation of part failures, and hence system breakdowns, is required to reduce or avoid the downtimes of machines and stock-outs. If detected sufficiently early, potentially broken parts of a machine may even lead to not necessarily having to store the respective spare part. For estimating the spare parts demand as accurately as possible, this article conceptualizes an approach for integrating condition monitoring information provided by Intelligent Maintenance Systems and forecasting methods. This concept is validated based on an example evaluation. Thus, the research objective is to improve the forecasting quality of estimated machine breakdowns in order to enhance the planning of the spare parts supply chain.

Analyzing and processing intelligent maintenance systems data to use for planning spare parts supply chains

“…Furthermore, with suchlike methods it is possible to forecast the spare parts demand from the point of view of a machine's operator at the end of the SPSC and not taking into account the position of a spare parts manufacturer. In summary, only the proposed concept of [12] might close suchlike research gap (For details about the analysis results and the concept see [12]). Hence, the concept of [12] might be a promising approach for determining accurate spare parts demand forecast results.…”

“…In summary, only the proposed concept of [12] might close suchlike research gap (For details about the analysis results and the concept see [12]). Hence, the concept of [12] might be a promising approach for determining accurate spare parts demand forecast results.…”

“…A detailed overview of the existing methods are provided in [11]. Hellingrath and Cordes [12] have broadened the literature survey of [11] by extending the classification regarding the usage of condition related information, identifying a few methods doing so (e.g. [13], [14], [15] and [16]).…”

“…Thus, the IMS must be capable of estimating a breakdown date of the respective part and determining the most suitable CDF that describes the probable breakdown date and breakdown probability. This data is needed for forecasting the spare parts demand at the spare parts manufacturer by using the approach proposed by [12]. Subsequently, the forecasted demand can be used in the context of the case study to reduce transport costs by bundling transports and to increase the availability of service personnel and equipment by reallocating them.…”

“…[13], [14], [15] and [16]). However, they only use the condition monitoring information as external conditions not adapting the forecasting methods [12]. Furthermore, with suchlike methods it is possible to forecast the spare parts demand from the point of view of a machine's operator at the end of the SPSC and not taking into account the position of a spare parts manufacturer.…”