The effect of autocorrelation on control charts performance and process capability indices calculation

2021 ◽  
Vol 8 (3) ◽  
pp. 283
Author(s):  
Martin Ková�™ ◽  
N.A. ík ◽  
Petr Briš
Keyword(s):  
Control Charts ◽  
Process Capability ◽  
Process Capability Indices ◽  
Capability Indices

scholarly journals Indian Food Specialties Limited

2002 ◽  
Vol 27 (1) ◽  
pp. 55-68
Author(s):  
Satish Y Deodhar ◽  
Devanath Tirupati
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Hazard Analysis ◽  
Process Capability ◽  
Process Capability Indices ◽  
Market Conditions ◽  
Quality Control Charts ◽  
Critical Control Points ◽  
Capability Indices ◽  
Indian Food

Indian Food Specialties Limited (IFS) introduced tools of food quality management in May 2000 in response to changing market conditions and poor profitability. Spoilage in the production process was very high and the company had incurred losses for three successive years starting from 1996-97. The company addressed quality concerns by introducing management tools such as quality control charts and process capability indices, and was considering implementation of a food safety system called Hazard Analysis and Critical Control Points (HACCP). The case describes the changing market conditions and the company's response to improving quality, and provides a learning exercise on quality control charts, process capability indices, and HACCP.

scholarly journals Combining Capability Indices and Control Charts in the Process and Analytical Method Control Strategy

2020 ◽  
Author(s):  
Alexis Oliva ◽  
Matías Llabrés
Keyword(s):  
Control Strategy ◽  
Analytical Method ◽  
Control Charts ◽  
Process Capability ◽  
Real Data ◽  
Process Capability Indices ◽  
Specification Limits ◽  
Capability Indices ◽  
And Control ◽  
Control Limits

Different control charts in combination with the process capability indices, Cp, Cpm and Cpk, as part of the control strategy, were evaluated, since both are key elements in determining whether the method or process is reliable for its purpose. All these aspects were analyzed using real data from unitary processes and analytical methods. The traditional x-chart and moving range chart confirmed both analytical method and process are in control and stable and therefore, the process capability indices can be computed. We applied different criteria to establish the specification limits (i.e., analyst/customer requirements) for fixed method or process performance (i.e., process or method requirements). The unitary process does not satisfy the minimum capability requirements for Cp and Cpk indices when the specification limit and control limits are equal in breath. Therefore, the process needs to be revised; especially, a greater control in the process variation is necessary. For the analytical method, the Cpm and Cpk indices were computed. The obtained results were similar in both cases. For example, if the specification limits are set at ±3% of the target value, the method is considered “satisfactory” (1.22<Cpm<1.50) and no further stringent precision control is required.

scholarly journals Concept of process capability indices as a tool for process performance measures and its pharmaceutical application

2020 ◽  
Vol 10 (5) ◽  
pp. 333-344
Author(s):  
Abikesh Prasada Kumar Mahapatra ◽  
Jianwu Song ◽  
Zhibo Shao ◽  
Tang Dong ◽  
Zihong Gong ◽  
...  
Keyword(s):  
Control Charts ◽  
Manufacturing Industry ◽  
Drug Product ◽  
Control Process ◽  
Process Capability ◽  
Process Capability Indices ◽  
Process Performance ◽  
Process Robustness ◽  
Capability Indices ◽  
Pharmaceutical Industries

The main objective of the present study is to present the concept of process capability and to focus its significance in pharmaceutical industries. From a practical view point, the control charts (such as X and R hart) sometimes are not convenient summary statistics when hundreds of characteristics in a plant or supply base are considered. In many situations, capability indices can be used to relate the process parameters. The resulting indices are unit less and provide a common, easily understood language for quantifying the performance of a process. Process capability indices (PCIs) are powerful means of studying the process ability for manufacturing a product that meets specifications. Several capability indices including Cp, Cpu, Cpl and Cpk have been widely used in manufacturing industry to provide common quantitative measures on process potential and performance. The formulas for these indices are easily understood and can be directly implemented. A process capability analysis compares the distribution of output from an in-control process to its specifications limits to determine the consistency with which the specifications can be met. The process capability is also having a significant role in pharmaceutical industry. Process capability indices can be a powerful tool by which to ensure drug product quality and process robustness. Determining process capability provides far more insight into any pharmaceutical process performance than simply computing the percentage of batches that pass or fail each year. Keywords: Process capability; Cp/Cpk; Pp/Ppk; Pharmaceutical quality, process robustness, specification

The Process Capability Analysis to Assess Capacity of a Cleaning Liquid Product with Asymmetric Tolerances

2020 ◽  
Vol 38 (6A) ◽  
pp. 910-916
Author(s):  
Sohaib Khlil ◽  
Huthaifa Al-Khazraji ◽  
Zina Alabacy
Keyword(s):  
Control Charts ◽  
Liquid Product ◽  
Process Capability ◽  
Process Capability Indices ◽  
Filling Process ◽  
Control Engineering ◽  
Normal Probability ◽  
Capability Indices ◽  
Capability Analysis ◽  
Asymmetric Tolerances

Process capability indices are a powerful tool used by quality control engineering to measure the degree to which the process is or is not meeting the requirements. This paper studies the application of process capability indices in the evaluation of a process with asymmetric tolerances. The analyzed collected data of the cleaning liquid “Zahi”, was used to investigate the ability of the filling process to meet the requested specifications. Matlab software was used to plot control charts, normal probability, and histogram of the data gathered from the production line and further performed statistical calculations. It was observed from the control charts that the filling process is under control. In addition, it was revealed by the process capability indices that the process of filling the cleaning liquid bottle is not fitted with the target value but it is adequate.

New multivariate process capability indices for measuring the performance of multivariate processes subject to non-normal distributions

2015 ◽  
Vol 33 (1) ◽  
pp. 42-61 ◽  
Author(s):  
Jeh-Nan Pan ◽  
Chung-I Li ◽  
Wei-Chen Shih
Keyword(s):  
Process Capability ◽  
Process Capability Indices ◽  
Process Data ◽  
Multivariate Process ◽  
Multivariate Processes ◽  
Content Type ◽  
Normal Distributions ◽  
Normality Assumption ◽  
Capability Indices ◽  
Multivariate Manufacturing

Purpose – In the past few years, several capability indices have been developed for evaluating the performance of multivariate manufacturing processes under the normality assumption. However, this assumption may not be true in most practical situations. Thus, the purpose of this paper is to develop new capability indices for evaluating the performance of multivariate processes subject to non-normal distributions. Design/methodology/approach – In this paper, the authors propose three non-normal multivariate process capability indices (MPCIs) RNMC p , RNMC pm and RNMC pu by relieving the normality assumption. Using the two normal MPCIs proposed by Pan and Lee, a weighted standard deviation method (WSD) is used to modify the NMC p and NMC pm indices for the-nominal-the-best case. Then the WSD method is applied to modify the multivariate ND index established by Niverthi and Dey for the-smaller-the-better case. Findings – A simulation study compares the performance of the various multivariate indices. Simulation results show that the actual non-conforming rates can be correctly reflected by the proposed capability indices. The numerical example further demonstrates that the actual quality performance of a non-normal multivariate process can properly reflected by the proposed capability indices. Practical implications – Process capability index is an important SPC tool for measuring the process performance. If the non-normal process data are mistreated as a normal one, it will result in an improper decision and thereby lead to an unnecessary quality loss. The new indices can provide practicing managers and engineers with a better decision-making tool for correctly measuring the performance for any multivariate process or environmental system. Originality/value – Once the existing multivariate quality/environmental problems and their Key Performance Indicators are identified, one may apply the new capability indices to evaluate the performance of various multivariate processes subject to non-normal distributions.

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