The Experts below are selected from a list of 174 Experts worldwide ranked by ideXlab platform

Abdulkadi Gullu - One of the best experts on this subject based on the ideXlab platform.

  • statistical process control in machining a case study for Machine tool Capability and process Capability
    Materials & Design, 2006
    Co-Authors: Ali Riza Motorcu, Abdulkadi Gullu
    Abstract:

    Abstract In this experimental study some statistical calculations have been made to eliminate quality problems such as undesirable tolerance limits and out of circularity of spherodial cast iron parts during machining. X – R control charts have been constructed on the data obtained from this manufacturing to discover and correct assignable causes, so that the Machine Capability (Cp) and the process Capability (Cpk) can be determined. In order to compare design tolerance on working drawings and attained tolerances on workpieces after machining five mass production lines were set up in a medium sized company. The results obtained from five X – R control charts and the data gathered from all production lines were processed and evaluated. At this stage of the study, it was observed that some parts were oval and out of tolerance limits, Machines and processes were insufficient and production was instable. Through machining data and follow up studies some assignable causes for faulty workpieces were discovered, and ovalness and out of tolerance limits problems were eliminated. In addition to these developments, surface roughness of Machined workpieces was improved. All these activities show that in small or medium sized companies statistical quality control can be useful component of production provided that sufficient finance and qualified personal are utilized.

Ali Riza Motorcu - One of the best experts on this subject based on the ideXlab platform.

  • statistical process control in machining a case study for Machine tool Capability and process Capability
    Materials & Design, 2006
    Co-Authors: Ali Riza Motorcu, Abdulkadi Gullu
    Abstract:

    Abstract In this experimental study some statistical calculations have been made to eliminate quality problems such as undesirable tolerance limits and out of circularity of spherodial cast iron parts during machining. X – R control charts have been constructed on the data obtained from this manufacturing to discover and correct assignable causes, so that the Machine Capability (Cp) and the process Capability (Cpk) can be determined. In order to compare design tolerance on working drawings and attained tolerances on workpieces after machining five mass production lines were set up in a medium sized company. The results obtained from five X – R control charts and the data gathered from all production lines were processed and evaluated. At this stage of the study, it was observed that some parts were oval and out of tolerance limits, Machines and processes were insufficient and production was instable. Through machining data and follow up studies some assignable causes for faulty workpieces were discovered, and ovalness and out of tolerance limits problems were eliminated. In addition to these developments, surface roughness of Machined workpieces was improved. All these activities show that in small or medium sized companies statistical quality control can be useful component of production provided that sufficient finance and qualified personal are utilized.

Yan Ran - One of the best experts on this subject based on the ideXlab platform.

  • Machine Capability sigma level evaluation and allocation method
    Proceedings of the Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science, 2019
    Co-Authors: Shengyong Zhang, Genbao Zhang, Yan Ran, Adrian Murphy
    Abstract:

    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.

  • The Sigma Level Evaluation Method of Machine Capability
    Communications in Computer and Information Science, 2018
    Co-Authors: Shengyong Zhang, Genbao Zhang, Yan Ran
    Abstract:

    Different tolerances causes multiple values of Machine Capability index(Cmk) in the traditional evaluation method of Machine Capability. On the basis of normal distribution, a new evaluation method of Machine Capability, the sigma level evaluation method, is applied to solve the problems above. Combined with the six sigma quality management method, the compensation coefficient \( \Delta_{\mu } \) and negative stability coefficient \( \Delta_{S} \) of the machining process are defined. Multivariate statistical analysis methods are used to analyze the dimensional accuracy dispersion of multi-characteristics parts processing. The subjective and objective combination weighting method is used to evaluate the Machine Capability of multi-characteristics parts. Taking the transmission housing processing as an example, the feasibility and superiority of the sigma level evaluation method are proved.

Shengyong Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Machine Capability sigma level evaluation and allocation method
    Proceedings of the Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science, 2019
    Co-Authors: Shengyong Zhang, Genbao Zhang, Yan Ran, Adrian Murphy
    Abstract:

    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.

  • The Sigma Level Evaluation Method of Machine Capability
    Communications in Computer and Information Science, 2018
    Co-Authors: Shengyong Zhang, Genbao Zhang, Yan Ran
    Abstract:

    Different tolerances causes multiple values of Machine Capability index(Cmk) in the traditional evaluation method of Machine Capability. On the basis of normal distribution, a new evaluation method of Machine Capability, the sigma level evaluation method, is applied to solve the problems above. Combined with the six sigma quality management method, the compensation coefficient \( \Delta_{\mu } \) and negative stability coefficient \( \Delta_{S} \) of the machining process are defined. Multivariate statistical analysis methods are used to analyze the dimensional accuracy dispersion of multi-characteristics parts processing. The subjective and objective combination weighting method is used to evaluate the Machine Capability of multi-characteristics parts. Taking the transmission housing processing as an example, the feasibility and superiority of the sigma level evaluation method are proved.

Hsin Wang - One of the best experts on this subject based on the ideXlab platform.

  • failure analysis of pinch torsion tests as a thermal runaway risk evaluation method of li ion cells
    Journal of Power Sources, 2014
    Co-Authors: Tianlei Li, Hsin Wang
    Abstract:

    Abstract Recently a pinch–torsion test is developed for safety testing of Li-ion batteries. It has been demonstrated that this test can generate small internal short-circuit spots in the separator in a controllable and repeatable manner. In the current research, the failure mechanism is examined by numerical simulations and comparisons to experimental observations. Finite element models are developed to evaluate the deformation of the separators under both pure pinch and pinch–torsion loading conditions. It is discovered that the addition of the torsion component significantly increased the maximum first principal strain, which is believed to induce the internal short circuit. In addition, the applied load in the pinch–torsion test is significantly less than in the pure pinch test, thus dramatically improving the applicability of this method to ultra-thick batteries which otherwise require heavy load in excess of Machine Capability. It is further found that the separator failure is achieved in the early stage of torsion (within a few degree of rotation). Effect of coefficient of friction on the maximum first principal strain is also examined.