Process Capability Assessment with Tool Wear: An Investigative Study

Jagadeesh, R.; Babu, A. Subash

doi:10.1108/02656719410051698

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…A similar exercise for C pmk has been done by , whereas the present author is investigating for the C pk index. Jagadeesh & Babu (1994) have investigated the problem of process capability assessment in the presence of tool wear. They have used four different methods of estimating the process variability σ 2 , and concluded that the results based on the different methods are not consistent.…”

Section: Autocorrelated Datamentioning

confidence: 99%

Basic Process Capability Indices: An Expository Review

Anis¹

2008

Int Statistical Rev

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A review of the four basic process capability indices has been made. The interrelationship among these indices has been highlighted. Attention has been drawn to their drawbacks. The relation of these indices to the proportion nonconforming has been dwelt upon and the requirement of the adequate sample size has been emphasized. Cautionary remarks on the use of these indices in the case of nonnormal distributions, skewed distributions, and autocorrelated data are also presented. The effect of measurement error on process capability indices has been dealt with in great detail. Copyright (c) 2008 The Author. Journal compilation (c) 2008 International Statistical Institute.

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Section: Autocorrelated Datamentioning

confidence: 99%

Basic Process Capability Indices: An Expository Review

Anis¹

2008

Int Statistical Rev

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“…Deleryd (1998) mentions that a factor that has contributed to increase the application of PC is its request by quality systems and improvement methodologies like ISO 9000 and Six Sigma. In addition, Jagadeesh and Babu (1994) mention that nowadays it is not quite logical to proceed with full-scale production without conducting a PC analysis.…”

Section: Introductionmentioning

confidence: 99%

Overall equipment effectiveness (OEE) and process capability (PC) measures

Garza-Reyes

Eldridge

Barber

et al. 2010

Int J Qual & Reliability Mgmt

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Purpose -Overall equipment effectiveness (OEE) and process capability (PC) are commonly used and well-accepted measures of performance in industry. These measures, however, are traditionally applied separately and with different purposes. The purpose of this paper is to investigate the relationship between OEE and PC, how they interact and impact each other, and the possible effect that this relationship may have on decision making. Design/methodology/approach -The paper reviews the OEE and PC background. Then, a discrete-event simulation model of a bottling line is developed. Using the model, a set of experiments are run and the results interpreted using graphical trend and impact analyses. Findings -The paper demonstrates the relationship between OEE and PC and suggests the existence of a "cut-off point" beyond which improvements in PC have little impact on OEE. Practical implications -PC uses the capability indices (CI) to help in determining the suitability of a process to meet the required quality standards. Although statistically a Cp/Cpk equal to 1.0 indicates a capable process, the generally accepted minimum value in manufacturing industry is 1.33. The results of this investigation challenge the traditional and prevailing knowledge of considering this value as the best PC target in terms of OEE. Originality/value -This paper presents a study where the relationship between two highly used measures of manufacturing performance is established. This provides a useful perspective and guide to understand the interaction of different elements of performance and help managers to take better decisions about how to run and improve their processes more efficiently and effectively.

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“…Some of them are Wheeler and Chambers [1992], Oakland [2003], [THOMPSON J;KORONACKI, 2002]; Dissertations and Ph.D. theses have also been written on the subject: [ZALEWSKI, 1995], [OLWELL, 1996]. Andrássyová et al [2012] deal with nonnormal data in the automotive industry; Jeang and Chung [2008] considered the influence of deterioration of product usage during its useful life in the SPC analysis; Quesenberry [1988] and Jagadeesh and Babu [1994] describe an approach to SPC that includes a tool wear process. SPC monitoring during production is necessary to prevent the shipment of defective products.…”

Section: A232 Statistical Process Controlmentioning

confidence: 99%

A new method of rigid assemblies stochastic 3D tolerance analysis including thermal performance.

Umaras¹

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Positional and orientation tolerances are specified in the components of a mechanical assembly and are of great importance in design, as they affect its quality, reliability, and cost. Tolerance analysis is a method of stacking the tolerances parts of an assembly to achieve an overall value in a given direction. The opposite approach is tolerance synthesis, or allocation, where the tolerances of the components are adjusted through a determined criterion for compliance with design constraints or for optimization purposes, such as cost reduction. The tolerance synthesis is generally performed when the results of a tolerance analysis process do not reach a design constraint requirement. The aim of this thesis is to propose a new method for tolerance analysis in a three-dimensional domain, including manufacturing simulation and consideration of functional thermal effects. A case study involving an internal combustion engine shows the efficacy of the method. Manufacturing simulation based on the Monte Carlo method provides a statistical distribution representation of process variation along a specified tolerance range. This resource can lead to optimization of the tolerance range of the mechanical assembly in each orthogonal direction and can also be a significant aid in design decisions and the selection of manufacturing processes. A feature of the proposed method is the consideration of geometric position tolerances as a function of orientation tolerances. The feature results in great accuracy at a high manufacturing volume. The method is application-oriented and can be applied effectively in the industry.

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Process Capability Assessment with Tool Wear: An Investigative Study

Cited by 7 publications

References 12 publications

Basic Process Capability Indices: An Expository Review

Basic Process Capability Indices: An Expository Review

Overall equipment effectiveness (OEE) and process capability (PC) measures

A new method of rigid assemblies stochastic 3D tolerance analysis including thermal performance.

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