Richard Batchelor, Jan/Feb 2010 - updated 2017. Awarded 'Paper of the Year 2010' by Engineering Designer (ED) journal.
Nearly half of the problems encountered in production are to do with DFM or production variability.
Correct tolerances, the responsibility of the product designer, prevent costly rework. A knowledge of the capability of a manufacturing process enables: educated tolerancing; constructive, realistic discussion with manufacturers; prediction of sigma levels; RFT manufacture.
The article illustrates how empirically sourced process capabilities supplied by Tolcap facilitate realistic tolerancing.
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Richard Batchelor, Sept/Oct 2010 - updated 2017. Originally published in ED, the journal of the Institution of Engineering Designers.
Engineering experience tells you a proposed 'cost saving' manufacturing shortcut will back fire - but how can an engineer argue costs with the commercial people?
The discussed technique was developed from concepts suggested by DFSS, Cpk, FMEA occurrence rating and severity scales, and the traditional 'Rule of 10'.
The article concludes with illustrations of the relative costs of failures occurring at different stages in production, and a case study estimating the costs of casting versus drilling holes in an aluminium assembly.
G.V.S.S. Sharma, P. Srinivasa Rao, B. Surendra Babu, Jan 2017.
Sharma, Srinivasa Rao and Surendra Babu found Tolcap a useful research tool, enabling them to obtain the process capable tolerances they required for their analysis.
Abstract: Process tolerancing based on the process capability studies is the optimistic and pragmatic approach of determining the manufacturing process tolerances. On adopting the define–measure–analyze–improve–control approach, the process potential capability index (Cp) and the process performance capability index (Cpk) values of identified process characteristics of connecting rod machining process are achieved to be greater than the industry benchmark of 1.33, i.e., four sigma level. The tolerance chain diagram methodology is applied to the connecting rod in order to verify the manufacturing process tolerances at various operations of the connecting rod manufacturing process. This paper bridges the gap between the existing dimensional tolerances obtained via tolerance charting and process capability studies of the connecting rod component. Finally, the process tolerancing comparison has been done by adopting a tolerance capability expert software.
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G.V.S.S. Sharma, P. Srinivasa Rao, B. Surendra Babu, July 2017. Tolcap utilizing research paper.
Abstract: This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improve-control (DMAIC) approach. By following the DMAIC approach, the C p, C pk and C pm showed signs of improvement from an initial value of 0.66, −0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.
Christopher S. Dodd, James Scanlan, Steve Wiseall, Intern. Journal of Production Economics, February 2016. TCE (Tolcap predecessor) utilizing research paper.
Abstract: Consider a production system where products are continuously manufactured and their features inspected for conformance within specification limits. If features are produced above or below the specification limits, they are either subject to rework or the product scrapped. Optimal mean setting may be applied to adjust the manufacturing means to influence the amount of rework or scrap produced, maximising profit. Within the production system, manufacturing and then inspecting each feature in turn is termed serial production, whereas manufacturing multiple features before inspection is termed parallel production. This paper develops a generalised expression to optimise the mean values of each feature (optimal mean setting), where n number of features are produced in any combination of serial and parallel operations. Previous literature is restricted to considering two features in parallel. The production of multiple features in combinations of serial and parallel operations is not fully considered. The new generalised expression is validated by showing it is consistent with specific cases from past literature. The approach is then applied to a practical example of a gearbox shaft, considering the expected profit of eight possible manufacturing sequences, as well as the deviation of the manufactured means relative to the design intent. The generalised expression is widely applicable in component design and manufacturing planning where the process capability index of features is below one. The generalised expression also forms the basis for trade-offs between profitability and minimising deviations of manufactured means, which is the subject of further development.
Stuart Kay Team Consulting Ltd, Cambridge, UK, June 2007. This paper originally appeared in the Journal of Medical Device Technology.
The author explains how his team utilize TCE (the original software from which Tolcap has evolved) in designing medical devices.
Don Day of Tec-Ease Inc, Dr Martin Raines and Professor Ken Swift of CapraTechnology Limited, March 2005. Originally published in Machine Design.
Quality costs may consume 25% of total revenues in manufacturing businesses, mostly from rework, scrap, warranty, product-liability claims, and recalls.
This article offers an introductionary explanation of process capable tolerancing (PCT) methodology. Followed by a, PCT methodology utilising, worked example explaining the cost saving achieved in the redesign of a fuel injecting bobbin.
Ken G Swift and Richard Batchelor, June 1996. Originally published in Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture.
Abstract: Around 80 per cent of the costs and problems of quality are created in product development. The paper overviews a knowledge-based design technique for the prediction of potential variability risks in component manufacture and assembly, and presents a method for linking the risk metrics to notions of design acceptability and potential costs of quality in production and service. The paper considers issues related to application of the work to industrial products and describes its coupling with failure modes and effects analysis.
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