Scheduling With Alternatives Machine Using Fuzzy Inference System And Genetic Algorithm.

As the manufacturing activities in today's industries are getting more and more complex, it is required for the manufacturing company to have a good shop floor production scheduling to plan and schedule their production orders. Industri pengeluarcim kini telah berkembang pesat dan aktiviti pengeluarannya semakin kompleks, dengan itu syarikat pengeluar memerlukan jadual lantai pengeluaran (shop floor) yang terbaik untuk merancang permintaan pengeluaran (product)

The Barriers and Critical Success Factor for Implementing Lean Manufacturing at SMEs

Small Medium Enterprise (SME) gives a big pressure on the management of their assets. Lack of expertise and awareness will become the major obstacles in achieving a better business strategy. Lean principles are applied in manufacturing and service industries extensively, but its success application in industry has been poor. The main objective of this study is to identify the Barrier for implementation of Lean Manufacturing (LM) at SMEs and to determine the Critical Success Factors (CSFs) for Implementation of Lean Manufacturing (LM) at SMEs. The data was collected using questionnaire and all the data was analyzed by using SPSS. There are 208 respondents involved in this study and the questionnaire is accepted with Cronbach‟s Alpha more than 0.7. From the new conceptual model created after KMO and Bartlett‟s Test, the researchers show there is one construct eliminated for both CSFs and Barriers. This study found that the construct for the Barrier for implementation of Lean Manufacturing at SMEs were related to resources, management, knowledge and financial. The construct for the CSFs for Implementation of Lean Manufacturing at SMEs were related to responsibility &amp; leadership, supplier, people management and resource. The proposed model from this study will only be suitable for SMEs in Pasir Gudang Industrial area.</p

The Evolution of Ergonomics Risk Assessment Method to Prevent Work-Related Musculoskeletal Disorders (WMSDS)

In the last few decades, numerous of ergonomics risk assessment method was developed. These method was developed to prevent work-related musculoskeletal disorders or WMSDs among the workers. Although there is variety of methods was available to identify the present of WMSDs but the accuracy of the measurements is based on the methods applications and limitations. Due to the complexity of factors such as inhomogeneity of the working activities, the sophisticated of measurement process, the diversity of cultures, incapable to accesses various body posture, and others problem that remain unsolved, the evolution of ergonomics risk assessment methods was never ended. To react with the demanding related with the WMSDs problems, ergonomics risk assessment methods become more advance in technologies. Parallel with the upcoming challenges of industry revolution 4.0, ergonomics risk assessment methods need to be transformed and adapted with the advance technology-based methods. The industries already to step ahead and starting to represent their production activities using robotics technologies, artificial intelligence (AI), biotechnology, and super-computer technologies. Therefore, ergonomics committee and practitioner should realize the opportunities and developed new ergonomics risk assessment method that integrated with the technologies. They need to be more accessible, understood, visionary, and modernize. The evolution of ergonomics risk assessment methods must be continuing and not rely with the traditional approach only

Exploratory Study on the Online Learning Understanding Based on Movement and Condition in Sitting Position

This research study the relationship between the understanding of online learning during Movement Control Order (MCO) due to pandemic Covid-19 and the movement condition through the sensor’s parameters sensed by smartphone. The studies carried out to track the student’s movement and conditions in sitting position while online class conducted and collect the data recorded by using smartphone sensors. The Apps AndroSensor is used to measure the Light intensity (lux), Orientation (axis x, y and z), Sound Level (dB) and Heart Rate (bpm). The understanding of online learning is measured using survey and questionnaire. The respondents that involves on this research are consists from different universities. Multiple Linear Regression was used to conclude the relationship between the parameters and the understanding of online learning. Total 60 students were involved in this study. Students that are selected has followed the criteria needed which are height, weight and age