The purpose of defect detection is to sort conforming and nonconforming products or services through mass inspection. Defect detection assumes that defects will be produced; through this model, defects are, in many ways,
expected. In this first stage of quality consciousness, there are no feedback loops or tools are available for correcting
the factors that created the defectives in the first place.Once a defect is produced, it is too late to do anything but
remove it from the process output [8].Products and production processes are always subject toa certain amount of variation [3,9]. Understanding the concept of the variation is essential to the successful implementation of process improvements [10]. In this paper, the effect of operational variables affecting the performance of the process will be investigated. The operational variables and their effect on the process performance have several forms. One of these effects is related to the quality of the saleable product; when it contains defects it is considered to not conform to required
specifications. These defects can be attributed, in some cases, to the capability of the system; in this case the
number of defects in each produced unit would appear consistent or in a consistent range, while, in some manufacturing environments where the number of defects per unit of saleable product is not in a consistent range, this can be attributed to variations in the process variables contained within the manufacturing system. These variations
differ from shift to shift, day to day, or month to month. In many manufacturing plants, the item rejected by
quality inspection contains a variety of defects. The word ‘reject’ is not a function of the number of defects on the produced item. An item with one defect is called a ‘rejected item’, as are items with two, three, or more defects. There is
no differentiation between them. However, although one defect in an item is expected, many defects in an item require further investigation and should not be classed as an ‘expected’ occurrence. The manufacturing companies have the potential to achieve considerable gains, where a tool is employed to measure the expected defects and set measurements for deviation. Following this, the effect of process variables causing defects on the product can be optimized to achieve the objective of minimum or zero defects.
The objective of the work in this paper is to define a methodology that consists of the following: identification of the source of quality defect on the product,
The purpose of defect detection is to sort conforming and nonconforming products or services through mass inspection. Defect detection assumes that defects will be produced; through this model, defects are, in many ways,
expected. In this first stage of quality consciousness, there are no feedback loops or tools are available for correcting
the factors that created the defectives in the first place.Once a defect is produced, it is too late to do anything but
remove it from the process output [8].Products and production processes are always subject toa certain amount of variation [3,9]. Understanding the concept of the variation is essential to the successful implementation of process improvements [10]. In this paper, the effect of operational variables affecting the performance of the process will be investigated. The operational variables and their effect on the process performance have several forms. One of these effects is related to the quality of the saleable product; when it contains defects it is considered to not conform to required
specifications. These defects can be attributed, in some cases, to the capability of the system; in this case the
number of defects in each produced unit would appear consistent or in a consistent range, while, in some manufacturing environments where the number of defects per unit of saleable product is not in a consistent range, this can be attributed to variations in the process variables contained within the manufacturing system. These variations
differ from shift to shift, day to day, or month to month. In many manufacturing plants, the item rejected by
quality inspection contains a variety of defects. The word ‘reject’ is not a function of the number of defects on the produced item. An item with one defect is called a ‘rejected item’, as are items with two, three, or more defects. There is
no differentiation between them. However, although one defect in an item is expected, many defects in an item require further investigation and should not be classed as an ‘expected’ occurrence. The manufacturing companies have the potential to achieve considerable gains, where a tool is employed to measure the expected defects and set measurements for deviation. Following this, the effect of process variables causing defects on the product can be optimized to achieve the objective of minimum or zero defects.
The objective of the work in this paper is to define a methodology that consists of the following: identification of the source of quality defect on the product,
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