Modelling robustness in serial multi-stage manufacturing processes

Mondal, Sankar Prasad; Maiti, J.; Ray, Pradip Kumar

doi:10.1080/00207543.2013.798052

Cited by 11 publications

(4 citation statements)

References 49 publications

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“…In the work mentioned above, sensitivity analysis for candidate process was conducted for evaluating stability and robustness in MMP using multivariate data. 35 And the sensitivity matrices (Jacobian matrices) were used to construct the variation models. However, these methods are all appropriate for large batch production with enough samples.…”

Section: Literature Reviewmentioning

confidence: 99%

Sensitivity analysis-based process stability evaluation for one-of-a-kind production

Jiang

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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Quality controlling and process stability evaluating for one-of-a-kind production are the key aspects in improving the major technical equipment production capability. However, it is difficult to find the relationships between upstream machining errors and the machining process conditions and the machining quality due to the samples’ insufficiency. A novel sensitivity analysis-based process stability evaluation for one-of-a-kind production is proposed to solve this problem. First, a variation evaluation model for one-of-a-kind production is established. Second, this model will be analyzed, and the safety and real feasible spaces are described with performance distribution analyses. Finally, the process stability index for one-of-a-kind production is calculated by comparing the relationship between the two spaces. Also, a case validates the effectiveness of the proposed method. It is expected that this paper would contribute to the research of innovative QC methods and process stability evaluation of one-of-a-kind production.

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Section: Literature Reviewmentioning

confidence: 99%

Sensitivity analysis-based process stability evaluation for one-of-a-kind production

Jiang

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Therefore, these methodologies for robust design and process optimization cannot be applied in capability evaluation for machining processes. To measure the robustness of multi-stage manufacturing processes, Mondal et al 33 adopted sensitivity matrices (Jacobian matrices) to construct the variation models in single-stage process. Nevertheless, their method is only appropriate for large batch production, because plenty of samples are required to estimate the standard deviation of controllable input variables.…”

Section: Literature Reviewmentioning

confidence: 99%

Sensitivity analysis–based dynamic process capability evaluation for small batch production runs

Zhou

Jiang

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Quantifying the current and expected future performance of a machining process no doubt is essential for continuous improvement of product quality and productivity. However, process capability evaluation for small batch production runs is a challenging work, because the assumptions required by traditional evaluation approaches based on statistical process control techniques are commonly not satisfied in real world. In this article, a sensitivity analysis–based process capability evaluation method for small batch production runs is proposed, and a new capability index is also presented correspondingly. In this method, an error propagation model between machining errors and input errors is first established using weighted least squares support vector machine. Then, the sensitivity distribution of machining errors versus input errors is characterized by a set of eigenvalues and eigenvectors in the variation space of input errors. Third, the safe variation space of input errors is solved according to the specification limits of quality characteristics. Finally, the process capability is evaluated by comparing the fitness between the safe variation space and the tolerance space of input errors. A practical case is addressed to validate the feasibility and effectiveness of the proposed method, and the results demonstrate that the method can measure a real small batch machining process effectively and get rid of the common assumption of independent and identical distribution, which is needed by traditional methods.

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“…It is evident from the literature that there are some studies where process capability is proposed to measure performance of a robust process. So, it is required to model their relationship to explore how process capability can be used as a surrogate measure of robustness (Mondal et al, 2012(Mondal et al, , 2013a.…”

Section: Review Of Literaturementioning

confidence: 99%

Process capability – a surrogate measure of process robustness: a case study

Mondal

2015

International Journal of Quality &Amp; Reliability Management

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Purpose – The purpose of this paper is to obtain a better understanding on robust performance of a hardening and tempering process producing component worm shaft used in the steam power plant. This research is capable to explaining the variation of process capability in terms of robustness. Design/methodology/approach – This paper proposed a methodology (a combination of simulation, regression modelling and robust design technique) to study robustness of a hardening and tempering process producing component worm shaft used in the steam power plant and process capability acts as a surrogate measure of robustness. In each experimental run, the values of responses and the corresponding multivariate process capability indices across the outer array are determined. The variation of process performance (process capability values) due to random noise variation is studied using a general purpose process control chart (R-chart). Findings – The results provide useful information in term of insensitiveness of the process against the noise (raw material and process noise) variation where the process capability acts as a surrogate measure of process robustness and explains the variation of process capability in term of robustness. Practical implications – This paper adds to the body of knowledge on robustness of a manufacturing process. This paper may be of particular interest to practicing engineers as it suggests what factors should be more emphasis to achieve robust (consistent) performance from the process. Originality/value – The originality of this paper lies within the context in which this study is to address key relationships between process robustness and process capability in a manufacturing industry.

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Modelling robustness in serial multi-stage manufacturing processes

Cited by 11 publications

References 49 publications

Sensitivity analysis-based process stability evaluation for one-of-a-kind production

Sensitivity analysis-based process stability evaluation for one-of-a-kind production

Sensitivity analysis–based dynamic process capability evaluation for small batch production runs

Process capability – a surrogate measure of process robustness: a case study

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