Abstract

The productivity and product quality of a shuttle loom are comparatively less than that of a shuttleless loom because of its high power consumption, more losses of energy, and fault susceptible picking mechanism. The economical commercialization of shuttle loom weaving requires systematic aspects of quality control which enable the mill to adhere to the methods of defect control methods. The current study focuses on the effectiveness of loom patrolling in minimizing fabric defects in the quality inspection department. The t-critical Value distribution of the recorded loom patrol defects and defects recorded in the quality inspection section were calculated to get the rejection region. The study demonstrated how much loom patrol minimizes the number of defects in the inspection department and emphasized loom patrolling as a decisive defect control method for shuttle looms. The t-critical value was calculated from the recorded data of the snap study done through direct observation, interview, and check sheet and these data were also analyzed using the Pareto technique, and focus group discussion. It was found that reed mark, temple mark, over pick and double pick were frequent in the shuttle looms. The causes of the defects were material, process, and human-related problems ranging from spinning section up to finishing section. Scientific Remedies were applied to avoid the successive coming of the faults and minimized the frequency of the defects significantly.

Highlights

  • Quality is essential for any manufacturing or service industry to guarantee sufficient market share and meeting customer satisfaction thereby winning customer loyalty

  • The current study focuses on the necessity of loom patrolling and its effectiveness in minimizing fabric defects in the quality inspection department

  • The static data were analyzed by calculating t-critical value distribution to justify whether Ha which stands for the hypothesis “the loom patrolling is effective for defect minimization in quality inspection room” or Ho which stands for no significance is true

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Summary

Introduction

Quality is essential for any manufacturing or service industry to guarantee sufficient market share and meeting customer satisfaction thereby winning customer loyalty. Model-based approaches are most suitable to fabric images with stochastic surface variations or for random textured fabrics for which the statistical and spectral approaches have not yet shown good results Model-based methods include autoregressive model, fractal model, Markov random field model, and the Texem model.[20] Human inspection is the traditional means to assure the quality of fabric. It helps instant correction of small defects, but the human error occurs due to fatigue and fine defects are often undetected. The static data were analyzed by calculating t-critical value distribution to justify whether Ha (alternative Hypothesis) which stands for the hypothesis “the loom patrolling is effective for defect minimization in quality inspection room” or Ho (no Hypothesis) which stands for no significance is true

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