Machine capability sigma level evaluation and allocation method

2019 ◽  
Vol 234 (14) ◽  
pp. 2771-2780
Author(s):  
Sheng-yong Zhang ◽  
Gen-bao Zhang ◽  
Yan Ran ◽  
Adrian Murphy
Keyword(s):  
Production Management ◽  
Evaluation Method ◽  
Process Capability ◽  
Multiple Characteristic ◽  
Multivariate Statistical ◽  
Sigma Level ◽  
Traditional Process ◽  
Process Factors ◽  
Capability Evaluation

The concept of process capability has been widely used in production management and quality control. However, applying traditional process capability evaluation method to machine capability cannot eliminate the influence of other process factors other than machine. To solve the problem, we propose the sigma machine capability evaluation method in this paper. First, multivariate statistical analysis methods are used to analyze the influence of all factors. Second, we deleted the non-normal data through sample fitting. Then, on the basis of normal distribution, we used the sample variance as the evaluation index to calculate the sigma levels of single characteristic and multiple characteristic parts. Last, we applied the sigma evaluation method and the traditional one to conduct a case study and compare their results, which proves the feasibility and superiority of the sigma level evaluation method.

Improvement of Process Capability in a Multistep Machining Process

2014 ◽  
Vol 926-930 ◽  
pp. 793-796
Author(s):  
Fang Zhu ◽  
Xiong Fei Huang ◽  
Bao Yu Ye
Keyword(s):  
Physical Model ◽  
Evaluation Method ◽  
Process Capability ◽  
Machining Process ◽  
Variation Propagation ◽  
Index Evaluation ◽  
Complex Variation ◽  
Capability Evaluation ◽  
Capability Improvement

The work in this paper will present a developed methodology for process capability evaluation and improvement in a multistep machining process. In this methodology, a physical model is developed to describe the complex variation propagation process throughout all steps in a multistep machining process. Then building on this physical model, a process capability index evaluation method is derived. A capability improvement procedure is developed to prioritize process improvement efforts based on the sensitivity analysis of process parameters. Finally, the effectiveness of the proposed methodology is demonstrated in a case study.

scholarly journals Multiple Process Capability Improvement Method based on Principal Component Analysis

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Guangqi Ying ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Yuxin Liu ◽  
Shengyong Zhang
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Evaluation Method ◽  
Process Capability ◽  
Principal Component ◽  
Component Analysis ◽  
Multiple Process ◽  
Improvement Method ◽  
Capability Evaluation ◽  
Capability Improvement

For the traditional multi-process capability construction method based on principal component analysis, the process variables are mainly considered, but not the process capability, which leads to the deviation of the contribution rate of principal component. In response to the question, this paper first clarifies the problem from two aspects: theoretical analysis and example proof. Secondly, aiming at the rationality of principal components degree, an evaluation method for pre-processing data before constructing MPCI using PCA is proposed. The pre-processing of data is mainly to standardize the specification interval of quality characteristics making the principal components degree more reasonable and optimizes the process capability evaluation method. Finally, the effectiveness and feasibility of the method are proved by an application example.

Calculation Method on Process Capability Index of True Position Based on Maximum Material Condition

2014 ◽  
Vol 915-916 ◽  
pp. 1456-1459
Author(s):  
Shuang Zhang ◽  
Jin Gang Gao
Keyword(s):  
Calculation Method ◽  
Evaluation Method ◽  
Process Capability ◽  
Process Capability Index ◽  
Related Individual ◽  
Capability Index ◽  
Material Condition ◽  
Tolerance Specification ◽  
True Position ◽  
Capability Evaluation

This paper focuses on process capability evaluation method for position tolerance under maximum material condition. Due to application of maximum material condition the position tolerance specification varies individually for each part, the approach of percentage normalization is introduced to calculate position process capability index. Bush is taken as an example, and true position percentage normalization of 30 parts are calculated. Considering the true position constitution relative to position tolerance at maximum material condition, related individual percentages are used to express the result and the same tolerance size 100% is obtained as for a unilateral tolerance. Process Capability index is calculated with Minitab software.

Sugar factory audits, debottlenecking and efficiency improvement

2020 ◽  
pp. 607-612
Author(s):  
Bernard Coûteaux
Keyword(s):  
Evaluation Method ◽  
Predictive Modelling ◽  
Cane Sugar ◽  
Sugar Factory ◽  
Low Energy Consumption ◽  
Process Simulations ◽  
Capital Efficiency ◽  
Potential Improvement ◽  
Primary Focus

This paper elaborates on the key solutions offered by De Smet Engineers & Contractors (DSEC) to optimize the efficiency of cane sugar producing and processing facilities. In order to meet customer needs, DSEC offers proprietary predictive models built using the latest versions of specialized software. These models allow factory managers to envision the whole picture of increased operational and capital efficiency before it becomes reality. An integrated energy model and the CAPEX/OPEX evaluation method are discussed as ways to estimate and optimize costs, both for new greenfield projects and revamping of existing factories. The models demonstrate that factory capacities can be successfully increased using equipment that is already available. Special attention is paid to crystallization and centrifugation process simulations and the potential improvement of the global energy balance. One case study shows the transformation of a beet sugar factory into a refinery to process raw cane sugar after beet crop season and the second case shows the integration of a refinery into a cane sugar factory. The primary focus of the article is optimization of the technological process through predictive modelling. DSEC’s suggested solutions, which lead to great improvements in a plant’s efficiency and its ability to obtain very low energy consumption, are discussed.

The Rapid Iterative Test and Evaluation Method (RITE)

2018 ◽  
Author(s):  
Michael C. Medlock
Keyword(s):  
Evaluation Method ◽  
Test And Evaluation ◽  
Original Case ◽  
Definition Of

This chapter begins with a discussion of the philosophy and then definition of the RITE method. It then delves into the benefits of this method and provides practical notes on running RITE tests effectively. The chapter concludes with an overview of the original case study behind the 2002 article documenting this method.

Research on Oil Depot Safety Evaluation Based on Dow Chemical Fire and Explosion Index Assessment Method

2013 ◽  
Vol 748 ◽  
pp. 1256-1261
Author(s):  
Shou Hui He ◽  
Han Hua Zhu ◽  
Shi Dong Fan ◽  
Quan Wen
Keyword(s):  
Production Management ◽  
Evaluation Method ◽  
Risk Index ◽  
Safety Evaluation ◽  
Assessment Method ◽  
Theoretical Ground ◽  
Potential Hazard ◽  
Process Unit ◽  
Safety Production ◽  
Fire And Explosion

At the present time, the Dow Chemical Fire and Explosion Index (F&EI) is a kind of risk index evaluation method that is comprehensively used in evaluating potential hazard, area of exposure, expected losses in case of fire and explosion, etc. As the research object to oil depot storage tank area, this article ultimately confirms establishing appropriate pattern of process unit as well as reasonable safety precautions compensating method, in order to insure the reasonableness of evaluating result, by means of selecting process unit, confirming material factor and compensating safety precautions, using F&EI method. This can provide the basis for theoretical ground in aspect of oil depot development and safety production management.

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