Optimization of incoming inspection processes for components of construction and road machinery based on statistical methods

Abstract

Incoming inspection of purchased components remains one of the least formalized links in the production of construction and road machinery: in practice, manufacturers tend to choose between full inspection and a single fixed sampling plan rather than differentiating suppliers and assemblies by risk. This article proposes an approach to optimizing incoming inspection that combines three tools: standardized statistical acceptance sampling plans by attributes and by variables, an assessment of supplier process capability through the Cp and Cpk indices, and a cost-of-quality model that weighs inspection cost against the cost of an escaped defect. Using an illustrative calculation built for a high-criticality assembly (a hydraulic cylinder), the article shows that differentiating inspection across three tiers of supplier process capability, while keeping the normative AQL level unchanged, reduces total inspection cost compared both with full inspection and with a single sampling plan that disregards supplier capability. The conditions under which the approach applies are discussed, along with its divergence from more flexible dynamic acceptance sampling schemes described in recent literature. The model nature of the calculation and directions for subsequent empirical validation are stated as limitations.