Safwati Ibrahim
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Preferred name
Safwati Ibrahim
Official Name
Safwati, Ibrahim
Alternative Name
Ibrahim, Safwati
Safwati, Ibrahim
Safwati, I.
Ibrahim, S.
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Scopus Author ID
57191950629
Researcher ID
GDL-1857-2022

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A Case Study of Coffee Sachets Production Defect Analysis Using Pareto Analysis, P-Control Chart and Ishikawa Diagram

2021-01-01 , Idris N.I. , Sin T.C. , Safwati Ibrahim , FadzliRamli M. , Rosmaini Ahmad

Nowadays, food and beverages companies in Malaysia are struggle to survive with their rival, hence improving quality and increase productivity are vital. This paper propose the method of analysis a coffee sachet production defectives by using statistical process control (SPC) tools and also to identify each types of defects with their root cause. This paper are using methodology of physical observation through examination of automated production flow line, then Ishikawa cause-and-effect diagram are created. The company valid information are obtained from the professional such as production managers, quality control executives and line supervisors, also staffs and operators that direct or indirectly involves the production line activities through interview and distributed feedback form. After that, a Pareto diagram analysis is done hence creating a control chart (p-chart) to illustrate the result analysis. The result shows there are high number of product defectives according to each type and waste production occur. The problem found was underweight, leaking, overweight, empty, unsealed and height out of the standard. The major causes of defectives coffee sachet and root causes of each defect types are specified which are human, machine, work methods, and materials. While the main root cause of underweight and leaking defect are caused by unskilled worker and improper adjustment at the machine each time before running the production.

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Defect Factor Analysis Using Statistical Process Control Analysis: A Case Study in Spices Defected Packaging Production

2021-01-01 , Idris N.I. , Tan Chan Sin , Safwati Ibrahim , Mohammad Fadzli Ramli , Rosmaini Ahmad

The problems faced by food and beverages in Malaysia are still the emergence of defect products in every production and it escaped from quality control checked thus it reaches the consumer. This study aims to analyze the variability of defects in the production line in XX Food Industries Sdn. Bhd., using p-chart control and fishbone diagram. This company produce a food spices products whether it is well within the control or not and looking for the factors that causing to the defect products. Data collection and information obtained from interviews and documentation for the number of products and production defects for three months in XX Food Industries. The methods used to analyze products quality control by using p-chart, one of the statistical process control and fishbone diagram to determine the cause of defects products. The defects that usually occur in the production line are types of packaging defects such as leaking sachets, eyemark on the sachet sealing, and less product fill in the sachet that cause lightweight sachet. Results showed that products quality control in XX Food Industries Sdn. Bhd. is still controlled by the largest type of defects that are leaking with defects percentage 46.3 and with 36.28% percentage of defects caused by eyemark. Then, followed by defect caused by lightweight is 17.5%. Factors causing defects products are human, machine, work methods, and materials. In this case unskilled worker and the material of the plastic wrapping for the spices packet are primary cause of defects products. This study is useful in providing useful information in identifying causes for rejection or defect analysis. This research also helpful in proposing optimal solution to be implemented for productivity and quality improvement.

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Product defect prediction model in food manufacturing production line using multiple regression analysis (MLR)

2021-07-21 , Illa I.N. , Tan Chan Sin , Fadzli R. , Safwati Ibrahim , Rosmaini Ahmad , Mohd Fathullah Ghazli@Ghazali

This paper aims to develop an improved general mathematical model by focusing on human factors variables that related to the product defect in the manufacturing production line. This is because many studies found that almost 40% of total defects resulted from the operator error and the defects are usually not obvious and neglected. The objective to have defect prediction mathematical model to satisfy as early quality indicator of the manufacturing flow production line and assist the quality control team in manufacturing industries. Thus, the human factor variables will be investigate thoroughly and final model can be used to predict product defect on the line to improve product quality. Product defects quantity are identified and analyzed to determine the potential predictors for developing the mathematical model. A case study is offered that illustrates in a spice packaging semi-automated production line the effect that complexity variables have on assembly quality. By using Minitab, Multiple Regression analysis is conducted to model the relationship between the input variables towards response variables. From the analysis, the predicted data showed reasonable correlation with the observed data improved with adjusted R-Sq from 2.6% to 7.9%. Hence, the regression equation obtain is selected to be the prediction mathematical model for defects based on human factor input variables.

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