Abstract
Designing appropriate quality-inspections in manufacturing processes has always been a challenge to maintain competitiveness in the market. Recent studies have been focused on the design of appropriate in-process inspection strategies for assembly processes based on probabilistic models. Despite this general interest, a practical tool allowing for the assessment of the adequacy of alternative inspection strategies is still lacking. This paper proposes a general framework to assess the effectiveness and cost of inspection strategies. In detail, defect probabilities obtained by prediction models and inspection variables are combined to define a pair of indicators for developing an inspection strategy map. Such a map acts as an analysis tool, enabling positioning assessment and benchmarking of the strategies adopted by manufacturing companies, but also as a design tool to achieve the desired targets. The approach can assist designers of manufacturing processes, and particularly low-volume productions, in the early stages of inspection planning.
Highlights
Manufacturing companies are increasingly focused on producing high-quality and fault-free products that meet customer needs
In in-process inspections, units are inspected during the production process [10,11,12,13], while in offline inspections, finished products are inspected after the production process is completed [10, 14]
The purpose of this paper is to address this gap by proposing a general framework to quantitatively assess the adequacy of in-process inspection strategies from the point of view of the effectiveness and cost
Summary
Manufacturing companies are increasingly focused on producing high-quality and fault-free products that meet customer needs. Few studies investigated the design of offline inspection strategies which can be suitable for low-volume manufacturing productions. A methodology to select the best compromise between the effectiveness and the affordability of alternative offline inspection strategies in a low-volume Additive Manufacturing (AM) production was proposed [7]. The framework and the tool proposed in this study were applied to the assembly of wrapping machines Such a process can be classified as a low-volume production, being the total number of customised machines produced in a year, typically, of about 50 units.
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