Mohamad Shaiful Ashrul Ishak
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Preferred name
Mohamad Shaiful Ashrul Ishak
Official Name
Mohamad Shaiful Ashrul, Ishak
Alternative Name
Ishak, M. S.A
Ishak, Mohamad Shaiful Ashrul
Shaiful, A. I.M.
Main Affiliation
Scopus Author ID
57214125417
Researcher ID
FBZ-1767-2022

Research Output
Now showing 1 - 3 of 3
  • Publication
    Development of variable-line balancing chart by risk assessment using Monte Carlo simulation
    (IOP Publishing, 2023)
    Mohd Shihabudin Ismail
    ;
    Mohamad Shaiful Ashrul Ishak
    ;
    Nor Zaiazmin Yahaya
    ;
    Muhammad Iqbal Muhammad Hussain
    ;
    Mohd Adzrie Radzali
    Line Balancing Chart is one of the most used lean tools for determining cycle time (CT) and lead time (LT) in the production line processes flow, from raw material input until finished product output. However, for traditional Line Balancing Chart, only the average (mean) CT and LT are considered which causing inconsistent performance of the actual production line throughput rate (productivity). In this study, Variable-Line Balancing Chart (V-LBC) is introduced by considering the dynamic CT and LT in a form of (Minimum, Most Likely (mean), Maximum) for each process involved in the production line. The risk assessment for Value-added (VAA) and non-value added (NVAA) events in the flow are also considered for this V-LBC. A Monte Carlo simulation by using @Risk software is utilized to simulate each process CT distribution capability. As a result, each process in the V-LBC could be represented in horizontal and vertical time variables that involve a variable CT (VAA and NVAA) and risk assessment using Risk Assessment-Failure Mode and Effect Analysis (RA-FMEA) approach. The actual root cause led to the process variation also could be identified more accurately from the V-LBC. Hence the correct action could be taken in order to reduce the variation which indirectly increase the production line productivity.
  • Publication
    Improvement of value stream mapping by integrating a Monte Carlo simulation: a conceptual model
    (Polish Academy of Sciences, 2023)
    Alaa Salahuddin Araibi
    ;
    Mohamad Shaiful Ashrul Ishak
    ;
    Muhanad Hatem Shadhar
    Value stream mapping (VSM) is a well-known lean analytical tool in identifying wastes, value, value stream, and flow of materials and information. However, process variability is a waste that traditional VSM cannot define or measure since it is considered as a static tool. For that, a new model named Variable Value Stream Mapping (V-VSM) was developed in this study to integrate VSM with risk management (RM) using Monte Carlo simulation. This model is capable of generating performance statistics to define, analyze, and show the impact of variability within VSM. The platform of this integration is under Deming’s Plan-Do-Check-Act (PDCA) cycle to systematically implement and conduct V-VSM model. The model has been developed and designed through literature investigation and reports that lead in defining the main four concepts named as; Continuous Improvement, Data Variability, Decision-Making, and Data Estimation. These concepts can be considered as connecting points between VSM, RM and PDCA.
  • Publication
    Advanced value stream mapping: development of a conceptual model considering variability in production processes
    (SAE International, 2023)
    Alaa Salahuddin Araibi
    ;
    Mohamad Shaiful Ashrul Ishak
    ;
    Muhanad Hatem Shadhar
    Recently, lean manufacturing (LM) practices are being combined with tools and techniques that belong to other areas of knowledge such as risk management (RM). Value stream mapping (VSM) is a well-known tool in showing the value, the value stream, and the flow, which represents the three lean principles. VSM and RM, when used in tandem with one another, are more advantageous in covering VSM issues such as the variability of production processes. In this article, a conceptual model that integrates the two is shown and explained. The model helps to generate scenarios of current state map (CSM) and future state map (FSM) in a dynamic way by identifying current and potential risks. These risks might happen in the future, bringing with it negative ramifications including not reaching the main objectives within the defined time. The model has been tested in a coffee production company belonging to health and food sector. The proposed model specified the ranges of variability through the drawing of CSM and FSM. This is quite a milestone because one of the challenges of VSM is that it is a static tool, and, as such, process variability cannot be captured appropriately. This new model is expected to overcome this drawback.
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