Shaliza Azreen Mustafa
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Preferred name
Shaliza Azreen Mustafa
Official Name
Shaliza Azreen, Mustafa
Alternative Name
Mustafa, Shaliza Azreen
Mustafa, S.A
Main Affiliation
Scopus Author ID
55655687300
Researcher ID
FQJ-1111-2022

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  • Publication
    Application of fuzzy failure mode, effect and criticality analysis (fuzzy FMECA) with extended rule of criticality ranking assessment: a case study in ghee and soap industry
    (AIP Publishing, 2023)
    Adel Ali Azawqari
    ;
    Rosmaini Ahmad
    ;
    Badiea Aswaidy M
    ;
    Shaliza Azreen Mustafa
    This paper presents the application of fuzzy FMECA for item criticality ranking assessment. A case study from Yemen's ghee and soap industry was used, which focuses on a critical production system of seaming process. The proposed fuzzy FMECA framework is divided into three main phases. The first phase is the FMECA procedure that is commonly applied with criticality analysis is performed based on risk priority number (RPN) calculation of severity (S), occurrence (O) and detection (D) parameters measures. The second phase is the estimation of RPN based on the fuzzy approach, which is carried out based on Gaussian membership function application. The third phase is the final criticality ranking assessment process to prioritize the production components under study. In this phase, an extended rule is introduced to avoid/minimize overlapping values in criticality ranking determination. A case study on a critical production system that consists of overall 32 components was used for framework validation. The MATLAB fuzzy logic toolbox was used to assist the fuzzification process towards RPN numbers estimation. The overall results of FMECA with comparison values of typical RPN and fuzzy RPN are presented. The discussion on the implications and benefits of the extended rule application towards final criticality ranking determination is then given.
      2  7
  • Publication
    Implementation of kanban-based fifo system to minimize lead time at automated optical inspection operation - A case study in semiconductor industry
    ( 2021-01-01)
    Krom P.
    ;
    Rosmaini Ahmad
    ;
    Shaliza Azreen Mustafa
    ;
    Tan Chan Sin
    This paper presents an improvement project in a semiconductor industry to minimize product lead time in automated optical inspection (AOI) operation. The Lean Thinking (LT) approach is applied to drive this improvement project, which it performed based on three main stages; observation, improvement and validation. Initial observation study found a significant cause of this problem (lead time). There have improper record and control mechanisms of receiving the product lots from production department, picking the products lots for inspection and restoring the products lots after inspection. Therefore, this not only cause the high and inconsistent lead time of products lot to be inspect (due to random rack location searching during picking and restoring processes) also the right sequence of product lots from one type to another that went through the AOI operation cannot systematically managed and controlled. In improvement stage, a production control system, namely Kanban-based First-In-First-Out (FIFO) system is proposed to solve the stated problem. Generally, Kanban technique applied in this research project is to systematically guide the inspection operator for performing AOI operation based on FIFO rule. There are two keys rules behind Kanban technique application; First is to record the sequence of the product lots that been received from production department and obtained the rack location for their temporary store. Second is to provide input information for the inspection operator to perform the activities picking and restoring in the right sequence of product lot direct to the rack location that has been stored before. Another technical mechanism included in Kanban-based FIFO system is the application of supermarket buffer system to minimize the wafer lot searching activity. In validation stage, the proposed solution has been tested within the period of one month. Results show that the searching times for picking and restoring the product lots has reduced to 77.0% and overall product lead time due inspection process has reduced 54.2%. The mechanism of Kanban-based FIFO system is then proposed to the top management of the case study company to be embedded with Internet of Thing (IoT) technology to support Industrial 4.0 evolution.
      22  1