Introduction of AHP Decision Model for Prioritizing Critical Risk of WMSD in the Automotive Working Environment

Work-related musculoskeletal disorders (WMSD) is one of the essential occupational diseases that is a frequent and prevalent pain complaint by automotive workers. The importance of decisions in WMSD risk factors is related to the type of job task and working environment. This paper introduces the AHP decision model as an ergonomics assessment tool to determine relative measures of significance and assess priority weights for different risk categories of WMSD. This paper broadly categorizes the identified risk factors for WMSD into individual, organizational, physical, and psychosocial factors. Organizational factors indicated the most critical ergonomics risk factors influencing WMSD growth among automotive component manufacturer workers. Meanwhile, exposure to physical demand at work (EPD) and high workload (HWL) are the most critical risk factors. Since the various risk factors occurring under each category may vary significantly from context to context, a practical method for assessing and determining some significance level is required. AHP analysis does this in WMSD risk factors in the automotive working environment and is used as an ergonomics assessment tool

Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing

Research in assembly optimisation is presently inclined towards integrative measures. Several benefits of simultaneously optimised Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) have been highlighted by researchers to have better solution quality, shorter time-to-market, and minimalised error during planning. Recently, several efforts have been made to realise integrated assembly optimisation. However, none of the published research considered the two-sided assembly line problem. This paper presents an integrated ASP and ALB optimisation in a two-sided assembly environment (2S-ASPLB), which is mainly adopted in automotive assembly process. In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. The computational experiments were conducted in a few stages, beginning with the identification of the best decoding approach for 2S-ASPLB. Next, the best MOMVO coefficient was studied, followed by comparing MOMVO performance with well-established multi-objective optimisation algorithms. Finally, a case study problem was presented to demonstrate applicability of the proposed model and algorithm in real-life problem. The results indicated that the priority factor (PF) decoding approach had better performance compared with others. Meanwhile, in comparison with well-established algorithms, MOMVO performed better in convergence and solution distribution. The case study results indicated the applicability of proposed 2S-ASPLB model and algorithm to improve line efficiency in assembly line. The main contribution of the research is a new 2S-ASPLB model and optimisation scheme, which can assist manufacturer in designing better assembly layout

The implementation of lean manufacturing and ergonomics in small medium enterprise – Case study

Productivity can be increased by eliminating of all wastes. The objective of lean manufacturing is to eliminate wastes. Commonly, there are seven wastes known as transport, inventory, motion, waiting, over processing, overproduction and defects. However, ergonomics is a process to improve the working posture by designing or arranging a workplace, system and material handling. The aim of this study is to improve the productivity through the integration of basic lean manufacturing and ergonomics in the food company. The walkthrough and distribution of questionnaire have been conducted in this company. Each activity was observed to identify non-value-added activity and work related muscular skeletal disorder (WMSD) that affect the productivity by using questionnaire, motion study and Rapid Upper Limb Assessment (RULA). The questionnaire result has shown that the most of wasted motion is in weighing and measuring activity. In addition, all workers in this process were affected by the musculoskeletal disorder at their neck and shoulder. All movement were simulated through Delmia software. The RULA score shows that the worker had experienced pain at the arm and wrist. The score also suggested that the process should be changed immediately. The changes might reduce the worker's pain and increase the productivity

Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization

Hybrid flow shop with energy consumption (HFS-EC) combine the flow shop scheduling and parallel machine scheduling problem with the aim to optimize energy utilization, besides regular makespan in the production scheduling. This paper optimizes an HFS-EC case study using Moth Flame Optimization (MFO). The case study has been conducted in a machine shop concentrating on three machining types; lathe, milling and deburring. The objectives were to optimize makespan and total energy consumption in the machine schedule. Optimization using MFO has been conducted and the results was compared with well-established algorithm like Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization. The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. Although there were other solutions with better individual optimization objectives, but results obtained by MFO compromised between minimum makespan and energy consumption. The proposed HFS-EC model and MFO algorithm has a great potential to be implemented in other scheduling case study due to benefit of reducing carbon emission and at the same time maintain the production output

Experimental of multi-holes drilling toolpath using particle swarm optimization and CAD-CAM software on PCB

A multi-holes drilling process is widely used in electronics industry to produce printed circuit board (PCB). Nowadays, millions of PCB need to be produced in a single day to support the technological growth in all aspects of life. In this industry, the most time-consuming process is to drill the holes on the board. According to a survey, the tool movement in multi-holes drilling process spent up to 70% of the machining time. Various approaches have been proposed to optimize the toolpath in multi-holes drilling process. Previously, a computational experiment has been conducted to identify the best meta-heuristic algorithm to optimize this problem. The finding shows that Particle Swarm Optimization (PSO) has outperformed other comparison algorithm to generate the best toolpath. This paper aim to validate the PSO performance through an experiment. For this purpose, the experiment consist of nine drilling problems has been conducted to compare the toolpath that generated by PSO and commercial CAD-CAM software. The results indicated that the PSO generated toolpath is consistently faster than CAD-CAM generated toolpath, with 5% average difference. This finding confirmed that PSO has a great potential to be used in this process

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Kerangka kerja untuk pelaksanaan sistem pembuatan lean di perusahaan kecil dan sederhana (PKS) bagi komponen automotif

Global competition has driven automotive component manufacturing Small and Medium Industries (SMIs) to improve their business competitiveness and performance through implementing lean manufacturing system (LMS). However, the low success rate towards lean manufacturing implementation in many SMIs has given a serious course of concern. This research is aimed at formulating and developing a framework for lean manufacturing implementation in SMIs. This framework is particularly significant because it is set in a context of assisting the SMIs on how to systematically implement LMS and thus improves the rate of success. This study identifies the lean manufacturing critical success factors (CSFs) and LMS practices that are. key facets to success in LMS implementation. Further, in this research, 24 LMS practices were categorises into three categories of inter related LMS practices basic, intermediate and advanced. Then, the research investigates the effects of CSFs and categories of LMS practices on manufacturing performance. In this study, a mixed method research design was employed where the quantitative and qualitative data were collected sequentially. In the first phase, the survey questionnaire was sent to 250 automotive component manufacturing companies and the response rate was 24.8% from large companies and 14% from SMIs. The empirical analysis showed there were positive relationships between CSFs and LMS practices. The results also indicate that three groups of LMS practices contribute substantially to the manufacturing performance. There were six CSFs which are really important to the SMIs in order to be successful in LMS implementation, such as: leadership and commitment, training and education, effective communication, continuous improvement and customer management. Whereas, in the second phase, a multiple case study was performed in four SMIs and two big companies of Malaysian automotive components so as to further refine and understand the general scenario of LMS implementation in automotive component manufacturing SMIs. The cross-case comparison among the studied SMIs and big companies had discovered similarities on three CSF top management commitment and leadership, quality management and lastly on training and education. Apart from that, these companies also faced two main LMS implementation barriers such as: lack of lean manufacturing knowledge and workers quit their job. Finally, the compilation of quantitative and qualitative inputs were synthesised to develop a comprehensive framework for LMS implementation in SMIs. This framework was validated in one of the selected SMIs and proven that the suggested steps were applied accordingly. As a contribution to the community, this framework may contribute to the body of knowledge for both practitioners and academics in LMS implementation. In terms of theory, the framework has important strengths because it has explicitly framed the relationship between CSFs, LMS practices and manufacturing performance

A case study of energy efficient assembly sequence planning problem

Energy efficiency has become an important issue in manufacturing industry, since it is one of the biggest energy consumers in the world. Despite the importance of energy efficiency, it is much obvious that the research in assembly sequence that focus on environmental aspect is still lacking. In Assembly Sequence Planning (ASP), the research on problem optimization is mainly demanded for the effective computational approach to determine the best assembly sequence. This paper presents a case study from an electronic product assembly that considers the energy utilization during assembly process. In particular, the case study focuses to reduce the idle energy utilization in assembly process. The case study was optimized using newly proposed Moth-Flame Optimization (MFO) and then being compared with well-frequent used algorithms including Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The result of the computational experiment test was divided into comparison of assembly layout between MFO proposed layout and existing layout. Besides, the statistical test involving Analysis of Variance (ANOVA) and post-hoc test of Fisher’s Least Significant Difference (LSD) were then conducted. The proposed MFO performed better in terms of the best minimum fitness (0.401681), average fitness (0.415308), standard deviation of fitness (0.022601), with appropriate computational time and power consumed. In meantime, the results also indicated that the case study was suitable in the development of energy efficient model for AS

Experimental Analysis on Martensite Formation of Low Carbon Steel During Rapid Cooling Process

Rapid cooling is one of the heat treatment techniques, which has been adopted in manufacturing sheet metal forming products such as structural beam and automotive parts. It involves heating of the carbon steel, and then followed by fast cooling process inside the cooling medium such as water and oil. Formation of martensites is beneficial to obtain stronger products. At present, it is most not really known how material thickness affecting martensite formation. Therefore, this study was conducted to study martensite formations inside low carbon steel for three selected part thicknesses; i.e 2, 4 and 6mm. Mild steel is one of engineering material that has been selected in this project which mostly used in many structural and vehicle components and other domestic applications [Machado, et al.]. At high temperature condition, material characteristic performs differently in comparing to normal room condition. Microstructure transformation is their advantage, in term of lower working force and higher material flow rate deformation. Top of that, it is able to produce high strength material, with an addition of a heat treatment process [Adnan, 2005]. Heat treated components can be extensively improved due to microstructure recrystalizations in rapid cooling process. It is known that carbon steels can be processed differently. From the previous studies, it was revelaed that the diffusionless transformations contribute to martensite formation which is the hardest microstructure in iron-carbon system [Wen et al., 2005]. The lowest hardness is obtained due to a diffusion transformation, which cause the ferrite and/or pearlite formation by a eutectoid reaction. Martensite is obtained during rapid cooling while ferrite and pearlite obtained from austenite during slow cooling near the equilibrium. On the other hand, with the applied cooling rate increasing, the transformed structure evolves from granular bainite, lower bainite, self-tempered martensite, to finally martensite without self tempering [Qiao et al., 2009]