A systematic review for computer based observational techniques for assessing exposure to risk factors for work-related musculoskeletal disorders

The objective of this review are to systematically examine the existing techniques of computer based observational method for assessing Work-related musculoskeletal disorders (WMSDs) and analysed them to the needs of different potential users. Articles related are searched and collected from scientific database starting from 1977 to 2016. Seven methods are identified for computer based observational techniques and from these methods, only three methods have been evaluated as the intra-observer reliability and five methods are evaluated as interobserver reliability where the average results are moderate to good agreement. For concurrent validity, five methods have been evaluated with moderate agreement. Some of the risk factors that related with WMSDs are; physical, psychosocial, work organization and individual factors. In addition, these existing techniques did not fulfil the criteria of reliability and validity testing during the development of these methods

Review on pen-and-paper-based observational methods for assessing ergonomic risk factors of computer work

Background: Computer works are associated with Musculoskeletal Disorders (MSDs). There are several methods have been developed to assess computer work risk factor related to MSDs. Objective: This review aims to give an overview of current techniques available for pen-and-paper-based observational methods in assessing ergonomic risk factors of computer work. Methods: We searched an electronic database for materials from 1992 until 2015. The selected methods were focused on computer work, pen-and-paper observational methods, office risk factors and musculoskeletal disorders. This review was developed to assess the risk factors, reliability and validity of pen-and-paper observational method associated with computer work. Two evaluators independently carried out this review. Results: Seven observational methods used to assess exposure to office risk factor for work-related musculoskeletal disorders were identified. The risk factors involved in current techniques of pen and paper based observational tools were postures, office components, force and repetition. From the seven methods, only five methods had been tested for reliability. They were proven to be reliable and were rated as moderate to good. For the validity testing, from seven methods only four methods were tested and the results are moderate. Conclusion: Many observational tools already exist, but no single tool appears to cover all of the risk factors including working posture, office component, force, repetition and office environment at office workstations and computer work. Although the most important factor in developing tool is proper validation of exposure assessment techniques, the existing observational method did not test reliability and validity. Futhermore, this review could provide the researchers with ways on how to improve the pen-and-paper-based observational method for assessing ergonomic risk factors of computer work

Risk assessment of Occupational Safety & Heath (OSH) hazards at small and medium enterprise (SME)

Most of SMEs industries refuse to provide and conduct safety program for the employees in order to cut the budget. Thus, this industries are exposed to the occupational safety and health (OSH) hazards. Therefore performing the Hazard Identification, Risk Assessment and Risk Control (HIRARC) method are important to control the hazards. The objective of this research was to review occupational safety and health hazards related to small to medium enterprises (SMEs) industry. Besides that, this research conducted to identify the OSH hazards related to the selected SMEs industry using HIRARC method and to propose a suitable risk control to prevent the hazards. The selected SME industries are located in Rompin, Negeri Sembilan in production of cendol. For this research, two method of hazard identification were selected that are workplace inspection and hazard identification checklist. A total of 8 hazards were identified from the production process. 50% of the risk level were classified as low and 50% classified as medium risk level. The most hazardous work activity is related to ergonomic problem that is back pain as most of the activities were repetitive for a long time. As a conclusion, recommendation has been proposed to eliminate the identified hazards such as elimination, engineering control and personal protective equipment based on the hierarchy of risk control

Identifying Unnatural Variation in Precision Rotational Part Manufacturing

In the manufacturing industry, it is well known that in-process variation is a major contributor to poor quality products. In order to fabricate a precise part, the source of unnatural variation (UV) needed to be properly identified, monitored and controlled while the process is running. In relation to this issue, this study aims to identify the error root causes of UV in bivariate process associated with statistical process control (SPC) chart patterns. In research methodology, in-process variation in manufacturing roller head component was discussed systematically based on real product of roller head, computer aided design (CAD) and statistical process control (SPC) chart patterns. Initially, the CAD software was used to model a precise rotational part, and to analyse the cause of UV. Then, the programming software was used to generate the artificial SPC data streams based on an established mathematical model. Data generation also involved linear correlation between two dependent variables (bivariate). The outcome of this study would be helpful for industrial practitioners as a database when applying SPC for monitoring bivariate process

Development of an ergonomic risk assessment tool for work postures

The most widely used method for assessing work-related musculoskeletal disorders (WMSDs) is still the observational method, mainly because it is inexpensive and practical for use in a wide range of workplaces. However, there are no tools available that cover the wide range of physical risk factors at workplaces. Most of the existing observational methods have not been extensively tested for their reliability and validity during the development process. Therefore, the main objectives of this study are to (1) to develop a new observational technique called the Workplace Ergonomic Risk Assessment (WERA) method and (2) to determine the reliability and validity of the WERA method. The study was conducted in two phases: development of the WERA paper checklist from scientific evidence and literature review (Phase 1) and development of the WERA software program using Visual Basic programming (Phase 2). In the validity trials, the relationship of the main WERA body part scores to the development of pain or discomfort was statistically significant for the wrist, shoulder, and back regions. This shows that the WERA assessment provided a good indication of work related musculoskeletal disorders which may be reported as pains, aches or discomfort in the relevant body area. In the reliability trials, the results of inter-observer reliability demonstrated moderate agreement among the observers (K=0.41) from the feedback survey about the usability of WERA tool. On the other hand, all participants were agreed that the WERA tool was easy and quick to use, applicable to workplace assessment for the wide range of tasks, and valuable at work. The WERA tool has been developed for both paper checklist and software program use. It can be used to identify the physical risk factors associated with WMSDs at workplaces

Control Chart Pattern Recognition Using Small Window Size for Identifying Bivariate Process Mean Shifts

There are many traits in the manufacturing technology to assure the quality of products. One of the current practices aims for monitoring the in-process quality of small-lot production using Statistical Process Control (SPC), which requires small samples or small window sizes. In this study, the recognition performance of bivariate SPC pattern recognition scheme was investigated when dealing with small window sizes (less than 24). The framework of the scheme was constructed using an artificial neural network recognizer. The simulated SPC samples in different window sizes (8 ~ 24) and different change points (fixed and varies) were generated to study the recognition performance of the scheme based on mean square error (MSE) and classification accuracy (CA) measures. Two main findings have been suggested: (i) the scheme was superior when recognizing shift patterns with various change points compared to the shift patterns with fixed change point, with lower MSE and higher CA results, (ii) the scheme was more difficult to recognize smaller window size patterns with increasing MSE and decreasing CA trends, since these patterns provided insufficient information of unnatural variation. The outcome of this study would be helpful for industrial practitioners towards applying SPC for small-lot-production. &nbsp

Control Chart Pattern Recognition Using Small Window Size for Identifying Bivariate Process Mean Shifts

There are many traits in the manufacturing technology to assure the quality of products. One of the current practices aims for monitoring the in-process quality of small-lot production using Statistical Process Control (SPC), which requires small samples or small window sizes. In this study, the recognition performance of bivariate SPC pattern recognition scheme was investigated when dealing with small window sizes (less than 24). The framework of the scheme was constructed using an artificial neural network recognizer. The simulated SPC samples in different window sizes (8 ~ 24) and different change points (fixed and varies) were generated to study the recognition performance of the scheme based on mean square error (MSE) and classification accuracy (CA) measures. Two main findings have been suggested: (i) the scheme was superior when recognizing shift patterns with various change points compared to the shift patterns with fixed change point, with lower MSE and higher CA results, (ii) the scheme was more difficult to recognize smaller window size patterns with increasing MSE and decreasing CA trends, since these patterns provided insufficient information of unnatural variation. The outcome of this study would be helpful for industrial practitioners towards applying SPC for small-lot-production. &nbsp

Computer based observational technoques for assessing exposure to risk factors for workrelated musculoskeletal disorders: A review

The aimed of this review is to make an overview of the current techniques for computer based observational methods in assessing Work-related Musculoskeletal Disorders (WMSDs).Articles related to computer based observational method for assessing WMSDs are searched and collected from scientific database starting from 1977 to 2016. Seven methods are identified for computer based observational techniques and from these methods, only three methods have been evaluated as the intra-observer reliability and five methods are evaluated as inter-observer reliability where the average results are moderate to good agreement. For concurrent validity, five methods have been evaluated with moderate agreement.There is no method for computer based observational techniques which cover all of the risk factors of WMSDs. In addition, these current techniques did not fulfil the criteria of reliability and validity testing during the development of these methods

Ergonomic risk factors associated with muscuslokeletal disorders in computer workstation

Ergonomics Risk Factors (ERFs) at computer works are commonly related to Musculoskeletal Disorders (MSDs) such as repetitive movements, doing work in awkward postures and static postures while prolonged seating at works. The main objective of this study was to investigate the ergonomic risk factors associated with MSDs among employees in computer workstation. In this study, the data were obtained by structured interview using self-reported questionnaire and direct observation. The results show that there is significant association between neck and stress score with musculoskeletal symptoms and among office workers. As a conclusion, by assessing ERFs at workplace, the effectiveness of workplace interventions can be evaluated without waiting for changes in the prevalence of MSDs

A systematic review of ergonomic risk factors associated with computer work-related musculoskeletal disorders in office workstations

This review aims to give an overview of ergonomic risk factors associated with computer work-related musculoskeletal disorders in office workstations. Data from 1990 until 2015 was revised using electronic databases.The overview based on computer work, office risk factors, musculoskeletal disorders, working posture, office components and office environment.Epidemiologic studies show that physical exposure has a moderate and strong association with Computer Work-Related Musculoskeletal Disorders.Sixteen items of risk factors with significant associations with body part exposure outcomes were identified. Ergonomic risks factors involved awkward postures , repetitive movement, excessive force and office environment.This study describes recommended posture angles as well as appropriate distance between office workers and office equipment