Product Defect Analysis in Almond Cookies using Statistical Quality Control
DOI:
https://doi.org/10.59247/ijase.v3i1.164Keywords:
Almond Cookies, Defect Analysis, Pareto Diagram, Quality Control, Statistical Process ControlAbstract
Quality control is an essential aspect of food production because product defects can reduce consumer acceptance, production efficiency, and economic value. Small-scale food industries often face challenges in maintaining product consistency due to limited quality control systems and resources. Therefore, this study aimed to characterize product defects and provide an initial evaluation of production-process variability in almond cookies produced by a small-scale food industry in Yogyakarta using a Statistical Quality Control (SQC) approach. A descriptive observational study was conducted on four production batches comprising 2,125 almond cookies. Data collected included production volume, number of defective products, and defect types identified through visual inspection using a check sheet. The data were analyzed using defect-rate calculations, Pareto analysis, and Statistical Process Control (SPC) using a p-chart. A total of 99 defective products were identified, corresponding to an overall defect rate of 4.66%, while the first-pass conformity rate was 95.34%. Pareto analysis identified shape nonconformity as the dominant defect, accounting for 45.45% of total defects, followed by topping damage (17.18%), color non-uniformity (14.14%), poor dough cohesion (13.13%), and structural breakage (10.10%). The three most frequent defect types accounted for 76.77% of all defects. The p-chart showed that the four observed batch proportions were within the calculated control limits (UCL = 7.40%; LCL = 1.92%). However, because only four production batches were observed, these control-chart results should be interpreted as an initial indication of process variability rather than definitive evidence of long-term statistical control. The findings indicate that shape nonconformity is the primary quality-improvement priority, while further monitoring using a larger number of production batches is required to establish reliable process-control limits and investigate the underlying causes of defects.
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