Development of a model to assess work efficiency based on activity energy expenditure and activity wasted energy in horizontal drilling task

• Main Author: Shokshk, Ali Ahmed Mansour
• Format: Thesis
• Language: English
• Published: 2020
• Subjects: Industrial efficiency; Exergy; Control engineering systems
• Online Access: http://psasir.upm.edu.my/id/eprint/92810/1/FK%202020%20111%20UPMIR.pdf; http://psasir.upm.edu.my/id/eprint/92810/

Despite robotics and mechanisation becoming more common in the industry, hand drilling is still widely used in furniture manufacturing, household work, construction work, aircraft manufacturing, and aerospace. MSDs that are caused by non-neutral postures of the wrist, back, and shoulder, and high forces applied during drilling have affected operators. Measuring worker efficiency offers a chance to understand the things that work well and whether further changes are needed. Work efficiency models in literature are few and done in different tasks and simulations. Factors affecting work efficiency in drilling are the tool weight, repetitive movements, awkward posture, and anthropometry. The ideal weight of the hand tool has been conflicted in literature. Preliminary study in this research found that repetitive movement was necessary to continue drilling without any tiredness. Criticism has been raised recently on the posture assessment methods as they do not focus on load and coordinated postures. The effects of weight and Maximum Grip Strength (MGS) on Activity Energy Expenditure (AEE) also differ in the literature. Therefore, the aim of this study was to develop a working efficiency model in horizontal drilling tasks based on AEE and Wasted Energy Activity (AWE). Ideal tool weight, ideal repeated cycle time (RCT), and 12 coordinated postures were investigated. This model also served to validate the AEE data through Rating Perceived Exertion (RPE) and Accomplishment Time (AT), and finally, to investigate the effects of anthropometry on AEE and work efficiency. AnyBody modelling system using Maximum Muscle Activity (MMA) was used to investigate the weight of the tool. AEE using Actiheart was used to find the ideal RCT and investigate the 12 coordinated postures. RPE using Borg scale and AT using stopwatch were used to validate the AEE data. Differences in means and repeated measures ANOVA were used to analyse the data. Results showed that a tool mass of 2 kg or less, and a 4-sec RCT were optimum. Working with shoulder flexion of 90° and trunk bent forward of 20° was the most awkward posture. Leg support provided more comfort to all postures. From the 12 coordinated postures, 6 were between light and moderate awkward postures. The rest of the postures were between hard and very hard. The correlations between AEE with RPE and AT were strong which are 0.923; P < 0.01 and -0.827; P < 0.01 respectively. Furthermore, AEE declined with the increase in the subject’s weight and MGS with R2 = 0.62 and 0.12 respectively. Individuals with more weight (fat free) and high MGS consume less AEE and are considered more efficient. Finally, posture work efficiency model was also developed. The 12 coordinated postures had different efficiencies from low to very high. This model can serve as a basis for a new method to assess posture based on physiological assessment. Furthermore, this finding is useful to save up the individual’s energy to work for a longer duration with less fatigue.