Wan Zuki Azman Wan Muhamad
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Preferred name
Wan Zuki Azman Wan Muhamad
Official Name
Wan Zuki Azman, Wan Muhamad
Alternative Name
Azman, Wan Zuki
Wan Ahmad, Wan Zuki Azman
Muhamad, Wan Zuki Azmanwan
Main Affiliation
Scopus Author ID
55860800560
Researcher ID
R-4128-2019

Research Output
Now showing 1 - 2 of 2
  • Publication
    Job Shop Scheduling Approach for Managing Tasks' Allocation Time in Factory
    ( 2020-12-14)
    Saidat S.
    ;
    Ahmad Kadri Junoh
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Zainab Yahya
    To date, in modern industrial competitions, there are several industries demanded a high quality in terms of efficiency, adherence of delivery dates, and speed to achieve a demand work. One company in Jordan, specialized to produce a glass utilizing advanced machines and high-quality raw materials, whereas, there is a difficulty to fulfill the coverage of local demands. This paper, the researchers aims for an improvement of glass factory to minimize the unnecessary issues. To do so, it requires an effective method in order to enhance the production process in factory. As stated earlier, the effective method is required in this study namely Job Shop Scheduling (JSS), it is appropriate method to be used to deal with unnecessary problems that usually occur and present a suitable schedule which can guarantee an optimal solution in terms of minimizing the completion time that required to complete the whole production flow. This study aims to enhance the flow of the production line by diminishing products operation time. Thus, recent studies highlighted the outcomes declination in the product operation time by saving 85 minutes using random search (RS) algorithm, and each production line by 75 minutes via classical computation method. Thereupon, solving classical job shop scheduling (CJSS) model, which related to the study case of this paper, via RS algorithm is more significant than classical computation methods.
      5  24
  • Publication
    Prediction of rainfall trends using Mahalanobis-Taguchi system
    (Institut Teknologi Bandung, 2024-04-30)
    Muhammad Arieffuddin Mohd Jamil
    ;
    Mohd Yazid Abu
    ;
    Sri Nur Areena Mohd Zaini
    ;
    Nurul Haziyani Aris
    ;
    Nur Syafikah Pinueh
    ;
    Nur Najmiyah Jaafar
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Faizir Ramlie
    ;
    Nolia Harudin
    ;
    Emelia Sari
    ;
    Nadiatul Adilah Ahmad Abdul Ghani
    Full comprehension of precipitation patterns is crucially needed, especially in Pekan, a district in Pahang, Malaysia. The area is renowned for its elevated levels of precipitation, making it imperative to precisely categorize and enhance the analysis of rainfall patterns to facilitate effective resource allocation, agricultural productivity, and catastrophe readiness. The variability of rainfall patterns is contingent upon geographical location, necessitating the collection of a comprehensive data set that includes several characteristics that influence precipitation to make reliable predictions. Data were collected from the Vantage Pro2 weather station, which is located on the UMP Pekan campus. This study used the RT method to classify rainfall and T-Method 1 to determine the degree of contribution of each parameter. Significant parameters were validated using a data set from the same type of weather station but in a different district. The results showed that the Mahalanobis-Taguchi Bee Algorithm (MTBA) is more effective than the Mahalanobis-Taguchi System (MTS) in finding the significant parameters, but the parameters were a subset of MTS Teshima. Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS.