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

Press machine process improvement by using DOE method

The purpose of this study is to improve the efficiency of press machine for producing finish good product thru design of experiments application. Press process is significant to improve since the output of the palm oil product will be divided into two which are palm oil and palm nuts. The objective of this study is to identify the best parameter setting for reduce broken nuts during press process thru adoption of the design of experiments method. A full factorial design with single replication has been used to study the effects of important parameters which are temperature, cone angle, cone pressure and percentage of water. The measurement of output response is identified as percentage of broken nut. Referring to the company specification, the percentage of broken nuts must not exceed than 7 %. Randomize experiments was conducted based on table generated thru Minitab software. Normal probability test was carried out using Anderson Darling Test and show that the P-value is 0.325. Thus, the data is normal since there is no significance different between the actual data with the ideal data. Referring to effect estimate value for each parameter, factor B (Cone Angle) was not significant. Thus the experiments were converted from 24 to 23 with two replications. Referring to the ANOVA, all of the factors are significant except the AC interaction since the P -value for each of parameters less than 0.05. From the main plot and interaction plot, the recommended setting for each of parameters were suggested as low level for temperature, low level for cone pressure and high percentage of water. The prediction model was developed thru regression in order to measure effect of output response for any changes on parameters setting. In the future, the experiments can be enhanced using two replications of experiment and Taguchi methods in order to do verification of result

Recycling of aluminium-developing design criteria for aluminium cans compressor

Aluminium used in beverage containers or cans is a sustainable material and can be recycled repeatedly. In Malaysia, the activities of collecting aluminium beverage cans for recycle normally involve a process of compressing aluminium cans manually in order to reduce storage space. The cans compression process is very time consuming and unproductive. In addition, there is no standard aluminium cans compressor tool that available in the market currently. As such, this paper aims to identify users' requirements on the potential tool that could be used to compress aluminium beverage cans, follows by transform the important users' requirements to a set of design criteria for the development of aluminium cans compressor. In line with this, six important factors that influence users purchase decision on household product were identified from literature review. The important factors were adapted into a questionnaire to collect and identify users preferred requirements on aluminium cans compressor via Voice of Customer technique. Subsequently, Pareto analysis and t-test were applied to define the most important and significant users' requirements that influenced user purchase decision. As a result, a list of important users' requirements is generated, which is also served as the design criteria for the development of a new aluminium cans compressor. Finding from the paper suggested that the most important design criteria for the potential aluminium cans compressor are consisted of safety, cost, performance and reliability requirements

Big Data Analytics for Early Detection and Prevention of Age-Related Diseases in Elderly Healthcare

The exponential growth of the elderly population poses considerable obstacles to healthcare systems on a global scale, hence requiring the implementation of inventive strategies to identify and mitigate age-related illnesses at an early stage. The primary objective of this study is to explore the use of big data analytics to improve healthcare practices. Specifically, the emphasis is on identifying possible risk factors and developing proactive treatments for senior citizens. The research technique used in this study is based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) declaration of 2020. This approach is utilised to ensure a thorough and transparent review of the relevant literature. Moreover, the use of Rstudio software is prevalent in the field of data processing, statistical analysis, and visualisation. By conducting a comprehensive examination of academic databases and medical literature, this study undertakes an analysis of a collection of pertinent papers to explore the significance of big data analytics in the early diagnosis and prevention of diseases in senior populations. The studies that have been chosen include a wide range of healthcare fields, such as cardiology, neurology, cancer, and geriatrics. This selection aims to provide a thorough comprehension of existing practises and identify any possible areas that may need more attention. The results of this study emphasise the significant impact that big data analytics may have on healthcare for the elderly. Using extensive and varied datasets, sophisticated analytical methodologies such as machine learning algorithms and data mining allow the detection of nuanced patterns and correlations that might function as precursors for age-related ailments

Knowledge quality effect on process based management effectiveness

The objective of this study is to examine the effect of knowledge quality (KQ) on process-based management effectiveness (PBME). The knowledge quality for effective process-based management is an increasingly important issue to the business community. The current review conducted on research work in Knowledge Management and Quality Management Systems field has shown that there are deficiencies in the current research domain which, investigation on knowledge quality and its effect on process-based management was not an interest of previous researchers. The deficiencies shed light for future research that explores in details the effect of KQ on PBME. This issue has initiated interest amongst academicians to empirically examine the effect of knowledge quality on the process-based management effectiveness especially on the ISO9001:2008 certified organization. This study has found that KQ has significant direct effect with PBME in the certified ISO9001:2008 organization. This is indicated by the path coefficients and t-statistics of the relationship between KQ and PBME using PLS-SEM. The results is in line with the opinion derived from semi-structured interview conducted and also accords with earlier research which showed that the quality of knowledge can improve the performance of the processes. The evidence from this result suggests that organization should emphasize on the quality of knowledge to increase the process-based management effectiveness

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