Statistical Analysis of Production Efficiency and Defect Characterization in Home Appliance Manufacturing: A 2024 Case Study of Vertical Display Units

Abstract: The present research paper is an extensive quantitative investigation of both daily and monthly production rates, and defect patterns of production in manufacturing of vertical fridges with a height of 13 feet and referred to as the General Company of Light Industry, Iraq in the year 2024. This study used statistical process control (SPC) techniques and Pareto analysis to test the data on production in four selected months (February, April, September, and October). The analysis indicates that the fixed production quantity of 40 units daily with the defect rates that are between 0.38 percent and 1.15 percent throughout the duration of the sample. Instability in power supply became the leading causal factor with 55.6 percent of all defects (n=15), then there was welding process errors (18.5% n=5), worker negligence (14.8% n=4), machine malfunctions (7.4% n=2), and material defects (3.7% n=1). Using the control charts, it was found out that the months of April 2024 were a statistically significant period that was out of control and that urgent corrective actions were needed. This study provides empirical data to the industry of industrial engineering to establish the functionality of the combined production-quality control systems in the appliance production situations. This paper ends with evidence-based proposals to apply the Six Sigma methodologies, preventive maintenance measures, and infrastructure stabilization solutions in order to meet the goal of operational excellence.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-21
DOI
https://doi.org/10.5281/zenodo.18747154
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

Statistical Analysis of Production Efficiency and Defect Characterization in Home Appliance Manufacturing: A 2024 Case Study of Vertical Display Units

Salman Hussien Omran, Muder Abdullah, Laith Jaafer Habeeb*, Mahmoud Abdul Razzaq Sa'i et al.
Zenodo (CERN European Organization for Nuclear Research)
Advanced Statistical Process Monitoring
article

Statistical Analysis of Production Efficiency and Defect Characterization in Home Appliance Manufacturing: A 2024 Case Study of Vertical Display Units

Salman Hussien Omran, Muder Abdullah, Laith Jaafer Habeeb*, Mahmoud Abdul Razzaq Sa'i, Hussain Ali Hussain
article en

Abstract

Abstract: The present research paper is an extensive quantitative investigation of both daily and monthly production rates, and defect patterns of production in manufacturing of vertical fridges with a height of 13 feet and referred to as the General Company of Light Industry, Iraq in the year 2024. This study used statistical process control (SPC) techniques and Pareto analysis to test the data on production in four selected months (February, April, September, and October). The analysis indicates that the fixed production quantity of 40 units daily with the defect rates that are between 0.38 percent and 1.15 percent throughout the duration of the sample. Instability in power supply became the leading causal factor with 55.6 percent of all defects (n=15), then there was welding process errors (18.5% n=5), worker negligence (14.8% n=4), machine malfunctions (7.4% n=2), and material defects (3.7% n=1). Using the control charts, it was found out that the months of April 2024 were a statistically significant period that was out of control and that urgent corrective actions were needed. This study provides empirical data to the industry of industrial engineering to establish the functionality of the combined production-quality control systems in the appliance production situations. This paper ends with evidence-based proposals to apply the Six Sigma methodologies, preventive maintenance measures, and infrastructure stabilization solutions in order to meet the goal of operational excellence.

Zenodo (CERN European Organization for Nuclear Research)
University of Baghdad (IQ), University of Technology - Iraq (IQ), WeldQC (United States) (US), Al-Muthanna University (IQ)
Industry, innovation and infrastructure
Openalex Percentile: Top 50%
Advanced Statistical Process Monitoring
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