Information model for assessing the impact of tactical material procurement risks on order fulfillment in make-to-order manufacturing

Abstract

Manufacturing businesses are showing increased interest in the issue of supply risks for materials and components. In recent
decades, numerous studies and reviews have been published on the subject of supply chain risks. However, most research examines
the global impact of risks on business as a whole and proposes a multi-level procedure for identifying, assessing, and developing risk
mitigation measures, which should be carried out in advance with the involvement of specialists and experts. Nevertheless in maketo-order manufacturing, it is important to assess the risks of material supply for individual production orders, at the same time taking
into account constant changes in production state and supply chains. The problem of assessing the risks of material supply gets even
more complicated at enterprises with a high mix of manufactured products. To solve the above-mentioned problems, the authors
propose an automated model for risks evaluation. The model is implemented as a component of the enterprise's information system
(ERP) and uses data from the technological, production, inventory, and logistics modules to calculate the probability of deviation in
order fulfillment time from the planned schedule due to potential disruptions in material supply chains. When executing the model, it
analyzes the production's material requirements in both volumetric and calendar terms, inventory levels, and the condition of supply
channels. The risks of delayed delivery for each material are expressed as the standard deviation of the delivery date from the
planned date and are calculated by composing the risks for segments (elements) of the supply chain, the risks for which are, in turn,
calculated based on performance data accumulated in the logistics module, with the possibility of introducing correction coefficients
and expert evaluations. The overall risk of order material supply is determined by summing up the delivery risks of individual
materials, expressed as the corresponding standard deviations. The model's results can be used for managerial decision-making in
production and procurement or for communicating expected order fulfillment times to customers. The model has been tested at an
enterprise in the electrical engineering industry.