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Attribute Chart

The Experts below are selected from a list of 75 Experts worldwide ranked by ideXlab platform

Siva Canagassababady – 1st expert on this subject based on the ideXlab platform

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Brian Burgess, M. Munir Ahmad, Siva Canagassababady

    Abstract:

    Abstract The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects.

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-Integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Munir Ahmad, Brian Burgess, Siva Canagassababady

    Abstract:

    The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects. ?? 2006 Elsevier Ltd. All rights reserved.

Nasreddin Dhafr – 2nd expert on this subject based on the ideXlab platform

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Brian Burgess, M. Munir Ahmad, Siva Canagassababady

    Abstract:

    Abstract The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects.

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-Integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Munir Ahmad, Brian Burgess, Siva Canagassababady

    Abstract:

    The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects. ?? 2006 Elsevier Ltd. All rights reserved.

Brian Burgess – 3rd expert on this subject based on the ideXlab platform

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Brian Burgess, M. Munir Ahmad, Siva Canagassababady

    Abstract:

    Abstract The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects.

  • Improvement of quality performance in manufacturing organizations by minimization of production defects
    Robotics and Computer-Integrated Manufacturing, 2006
    Co-Authors: Nasreddin Dhafr, Munir Ahmad, Brian Burgess, Siva Canagassababady

    Abstract:

    The work in this paper will present a developed methodology for quality improvement in manufacturing organizations. This methodology comprises a model for the identification of various sources of quality defects on the product; this model would include an analysis tool in order to calculate defect probability, a statistical measurement of quality, and a lean manufacturing tool to prevent the presence of defects on the product. The attribution of defects to their source will lead to a fast and significant definition of the root cause of defects. The techniques described in this paper were developed for an improvement project in a plastic parts painting manufacturing facility of a first-tier supplier to the automotive industry. Data were collected from the manufacturing plant, which indicated that the daily defect rates were significant, ranging between 10% and 15%. These figures gave a clear indication that the number of defects could be significantly reduced to a few parts within the total production. This could be achieved if appropriate manufacturing practices were adopted with the aim of reducing the effect of manufacturing system variables that affect overall quality. A process Attribute Chart (H-PAC) has been introduced to monitor the defects every hour. Upper and lower control limits were given and an SPC graph is plotted every hour for the three major defects. If the defects go above the upper control limits, the team meets to solve the issues. Over ten weeks’ study after implementing changes, there was a 9% reduction in defects. ?? 2006 Elsevier Ltd. All rights reserved.