International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 01, January 2019, pp.1014-1025, Article ID: IJMET_10_01_105 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=1 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed ERGONOMIC DESIGN AND RULA ANALYSIS OF A MOTORISED WHEELCHAIR FOR DISABLED AND ELDERLY Bobby P Paul Assistant Professor(Sr.), SAINTGITS College of Engineering, Kerala, India Research Scholar, Karunya Institute of Technology and Sciences, Coimbatore, India Darius Gnanaraj S Professor, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India Sam Paul Professor, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India ABSTRACT Motorised Wheelchair plays a pivotal role in the social life of Persons with disability (PwD) or elderly. Indian Motorised Wheelchair users scuffle to identify right Ergonomic Motorised Wheelchair because there are only very few designs developed by Ergonomic approach. The paper describes the methods to design an Ergonomic Motorised wheelchair and analyzes the design with Human Digital Models(HDM). Authors also demonstrate analyses of user comfort and some Ergonomic design methods. The analysis of user comfort while in the design stage using a Manikin by applying Indian Anthropometric Data makes the wheelchair a better fit for the Indian users. Thus, the design of user-friendly wheelchairs by HDM Ergonomic analysis. Authors also discuss RULA analysis of Motorised Wheelchair with 5th, 50th and 95th percentile HDM. The paper also estimates Indian Anthropometric Dimensions on HDM for Motorised Wheelchair. The paper also presents some design innovations on the footrest Keywords: Assistive Technology· Motorised Wheelchair CATIA RULA·Human Digital Models· Ergonomic Work Bench. Cite this Article: Bobby P Paul, Darius Gnanaraj S and Sam Paul, Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly, International Journal of Mechanical Engineering and Technology, 10(01), 2019, pp.1014-1025. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=1 1. INTRODUCTION http://www.iaeme.com/IJMET/index.asp 1014 editor@iaeme.com Bobby P Paul, Darius Gnanaraj S and Sam Paul Motorized Wheelchair use rose to remarkable numbers due to the rise in the aging population. Data from WHO shows 15% of the world population lives with some form of disability and 24% experience severe difficulties in functioning [1]. India reported 20 million people in 2012 with disabilities, out of that, 11 million are locomotors disabled. Statistics in rural areas shows approximately 1046 per 100,000 people and urban areas 901 per 100,000 people with are locomotive disability [2]. Analysis of cost benefits of the ergonomic wheelchair is a challenge because of the difficulty in collecting data on costs and benefits. The scarcity of data is also another difficulty, as the motorized wheelchairs are uncommon [3]. In the past product-designers ignored the ergonomic requirements of the product in the conceptual stage. However, further Ergonomic analysis is kept aside until a prototype. Designers also neglected Ergonomic analysis as suitable virtual tools were unavailable. The advancement of computers and the ability to compute faster brought significant improvement in Software and its applications in different areas of Engineering. Computational Ergonomics also leaped, and now it is not mere calculation by formulas, questionnaires, filling up tables or accumulating empirical data. Instead, Human Digital Models (HDM) started a new phase of computer-aided design technology. CATIA caters a variety of Ergonomic tools by using Human Digital Models. HDM can aid computational analysis on human-machine interactions and facilitates better ergonomic designs in the absence of real users [4]. Motorized wheelchair users are susceptible to lower back and other Musculoskeletal Disorders (MSD) [5,6]. Ergonomic Motorized Wheelchairs designed for reducing repetitive stress injuries, increased comfort, and safety of wheelchair users. Ergonomic Wheelchairs improves the user experience while travel, getting on and off and in rough surfaces. Applying Ergonomics is one of the significant challenges as the users are either lower limb disabled or with some other severe disability on their motor functions. Analysis of cost benefits before and after applying Ergonomics is a significant challenge for designers [3]. Literature shows that the exposure of the wheelchair user to injuries is proportional to the wrong movements he makes while shifting to and from the wheelchair. Long-term injuries for wheelchair users are back pain or pain on hands and wrist while using the joystick for a more extended period. The right form of lower back and wrist support can improve user safety, comfort and reduce longterm Musculoskeletal injuries. Introduction of DHMs to represent the wheelchair user sitting, and applying the right anthropometric data improves the design of the Motorized wheelchairs [7]. RULA analysis using HDM makes the design process manageable and economical. The paper discusses the process of Ergonomically optimizing the design using CATIAHuman Digital Models and details on possible design changes, which makes it Ergonomic and user-friendly. HDM made of Indian Anthropometric Data is placed on the Motorised Wheelchair, and RULA analysis asses the user discomfort. After RULA analysis, exact locations of discomfort are redesigned to increase the comfort of the user. Figure.2 in the paper shows methods adopted for the Ergonomic Design of Motorised Wheelchairs using Human Digital Models. 2. DESIGN METHODS 2.1. Folding Hinge One purpose of the Motorised Wheelchair design is to enhance the fold-ability. Figure 1 shows the Motorised Wheelchair folding hinge for the multipurpose ladder joints. The four legs and the seat are on hinges as in Fig.9(a, b&c). The steel hinge can bare load up to 150kg. The weight of one hinge is 1.05kg and thickness of the plates used to manufacture the hinge is 2mm. The Motorised Wheelchairs uses hinges with self-locks for saftey[8]. http://www.iaeme.com/IJMET/index.asp 1015 editor@iaeme.com Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly Figure 1 Hinge with Locks Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly 2.2. Ergonomics in CATIA The motorized wheelchair comfort depends on material quality, structure, shape, handling, and stability. Structure and shape in the design of motorized wheelchair depend on available Anthropometric data of users, as Indian Anthropometric data is available in book form[9]. CATIA Ergonomic Work Bench can be of aid for Ergonomic analysis of Wheelchairs. CATIA is the fist of its kind to suggest computational study by Human Digital Model to analyze man-machine design [4]. Figure 2 shows the methodology adopted for the design of Motorized Wheelchair by Human Digital Model using CATIA. RULA (Rapid Upper Limb Assessment) virtually analyses user comfort on Motorized Wheelchair Design. There are four modules in CATIA for Ergonomic Design and Analysis, Human Measurement Editor Module (HME), Human Action Analysis Module (HAA), Human Posture Analysis Module (HPA) and Human Builder Module (HBM). HME, HPA & HBA is used to analyze the user comfort in Motorized Wheelchair. Indian Anthropometric Data for sitting posture is applied to HDM using HME. RULA analysis uses HBM and HPA for appropriate postures. RULA is repeated on the wheelchair model until the score turns acceptable for the design [4, 10]. The flow chart shows the steps for optimizing a model using RULA. http://www.iaeme.com/IJMET/index.asp 1016 editor@iaeme.com Bobby P Paul, Darius Gnanaraj S and Sam Paul Figure 2 RULA Analysis using CATIA - Methodology 2.3. Concise Description of Human Activity Analysis The activities are pushing, pulling, lowering, effects of lifting, and comfort while sitting are analyzed and optimized by Human Activity Analysis. CATIA Ergonomic analysis does not require a real workplace or a person to execute. The virtual analysis in CATIA can investigate and improve products and workplaces. Human Activity Analysis uses Manikin to evaluate postures by a range of tools and methods in the digital environment. The designer can virtually test and improve the design by applying different techniques. The Ergonomic fit of Human Manikin determines product shape, size, and dimensions [11]. 2.4. RULA on Assessment Sheet vs RULA Assessment in CATIA Rapid Upper Limb Assessment (RULA) analyzes the upper extremity ergonomic risk factors. The purpose of RULA is to check bio-mechanical and postural load requirements for the neck, trunk, and upper extremities. The RULA assessment sheet is a single page worksheet, used to assess the force, posture, and repetitions of work. In RULA worksheet, section A assesses arms, wrists and section B assess of the neck and trunk. The score for sections A & B is totaled to assess the risk of MSD. RULA analysis by mere observation, the results could slightly vary from person to person. Manual RULA assessment is a single sheet of postures and scores [12–14]. The digital RULA score complies for the Manikin. Once we place the HDM on the digitally modeled workplace or product, the whole analysis that is conducted by observation is just within reach of a single mouse click. According to analysis, the postures of the Manikin varies. Optimize criteria in I.K Behavior panel, aids to optimize posture for RULA analysis or Postural score. RULA Analysis tool is launched to select Manikin. Figure 3(a) shows criteria for conducting RULA analysis in CATIA. The side of HDM to analyze and predetermined best-suited posture is selected. There are three types of postures, Static, Intermittent, and Repeated. http://www.iaeme.com/IJMET/index.asp 1017 editor@iaeme.com Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly Table 1 5th, 50th and 95th Percentile Indian Male Anthropometric Dimensions for Human Digital Models [9]. Variables (Sitting) 5th mm 50th mm 95th mm Input Method Sitting Height 812 844 893 Manual Eye Height, Sitting 710 738 799 Manual Hip Breadth, Sitting 272 331 405 Manual Shoulder-Elbow Length 306.311 340.167 386.54 Foot Breadth Automatic 83 94 106 Manual 1537 1648 1781 Manual Variables (Standing) Stature Axilla Height 1129.39 1222.92 1332.583 Automatic 4 Waist Height 894 970 1053 Manual Chest-Height, Standing 1088 1180 1282 Manual Crotch-Height, Standing 675 765 849 Manual Acromion-Radial Length 281 312 356 Manual Radial-Stylion Length 207 243 289 Manual Sleeve out seam 484.823 547.383 629.404 Automatic Chest Breadth 259 298 356 Manual Waist Breadth 231 259 317 Manual Hip Breadth, Standing 272 331 397 Manual Intermittent repeat the tasks less than or equal to four times in one minute. Static and Repeated option in posture repeats the task greater than four times in one minute. In the same posture option, we can select Arms Supported/Person leaning; Arms are working across Midline and check Balance. Each should select according to the situation of the analysis. In the http://www.iaeme.com/IJMET/index.asp 1018 editor@iaeme.com Bobby P Paul, Darius Gnanaraj S and Sam Paul parameters, 'Load' is filled to specify the load of the object manipulated by the person. The score box shows the final score. Score range of each body part is in Fig 3(b). The risk factors such as, which are the number of movements, static muscle workforce, working posture and time, worked without a break is assessed in RULA analysis. Score 1 to 2 is color-coded in green indicates the posture is acceptable. (b) RULA Score Range (a) RULA Score Sheet Figure 3 RULA Score Card & Range Score 3 to 4 (Yellow) indicates further investigation or some minor design changes. Score 5 to 6 (Red) suggests immediate action by design change. The job of a design engineer is to make modifications and bring the score within acceptable range 1 to 2 or (Green) [5, 15]. In the paper, selects left and right sides of the manikin with posture as ’intermittent’ and ’arms supported’ for analysis. 2.5. Preparation of Human Digital Model for Analysis HDM for RULA analysis requires dimensions of human size. Human size varies with ethnicity, gender and age group.[16, 17]. Anthropometric data is available for HDM in CATIA for American, Canadian, French, Japanese and Korean. If the absence of data in software, a Manikin can be made by entering available data. The manikin posture is made sitting if the analysis is for sitting posture. Sitting posture for Manikin is by selecting the option in the product. Figure 4(a)& 4(b) shows ways to apply HDM with Indian Male Anthropometric dimensions of 5th, 50th, 95th Percentile for having the size of Indian Manikin [4, 15, 9, 18]. Each Manikin dimension can change in the Software or can set to automatic by the software by considering other dimensions. Table 1. shows the 5th,50th and 95th Percentile Indian Male Anthropometric Dimensions for three types of Human Digital Models. Posture also can change for the Manikin according to sitting posture as shown in Fig 4(c&d). The analysis on a motorized wheelchair, so the angle of the foot as 70 [19] as in Fig.4(c). The angle of the leg or any other body parts can change using posture editor as shown in Fig 4(d)[4]. 3. RESULT http://www.iaeme.com/IJMET/index.asp 1019 editor@iaeme.com Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly 3.1. RULA Analysis Results RULA Analysis by placing 5th Percentile HDM on the Motorised Wheelchair: Figure 5(a) shows the HDM with 5th per-centile anthropometric dimensions on the motorized wheelchair with the arm supported on hand rest. The fingers are adjusted to place on the Joystick. The analysis returned acceptable overall score 2 for the model. Only the wrist on left side Fig.5(b) returned a score 2 for further investigation. The overall score of posture A is 2 because of the wrist score 2 (a) Assign Dimensions-Sitting Manikin (b) Assign Dimensions-Standing Manikin (c) Angle of Foot-70 (d) Posture Editor Figure 4 Getting Manikin Ready for RULA Analysis The score of posture B is 2 as it suggests improvements in Wrist, Arms and Trunk support. RULA score on right side Fig.5(c) is same as in left except wrist has a Score of 3 which requires attention as per scorecard [5, 20, 21]. For RULA of 5th percentile, the seat to footrest height was reduced to 283mm instead of 313mm. http://www.iaeme.com/IJMET/index.asp 1020 editor@iaeme.com Bobby P Paul, Darius Gnanaraj S and Sam Paul (a) 5th Percentile HDM Side (b) RULA Score of Left Side (c) RULA Score of Right Figure 5 RULA Analysis with 5th Percentile Manikin RULA Analysis by placing 50th Percentile HDM on the Motorised Wheelchair: The RULA Analysis 50th percentile HDM in Fig.6 (a) scores better than that of 5th percentile. Both left and right side of the wrist scored to improve the design as in Fig.6 (a&b). Posture A scored 2, but posture B scored 1, which shows a person comes under 50th percentile has a better score on the Motorised Wheelchair. Thus, Wheelchair dimensions justify for 50th percentile HDM with acceptable score 1(Left) and 2(Right). (a) 50th Percentile (b) RULA Score of Left Side (c) RULA Score of Right Side Figure 6 RULA Analysis with 50th Percentile Manikin RULA Analysis by placing 95th Percentile HDM on the Motorized Wheelchair: The 95th percentile manikin as in Fig.7(a). The analysis on left side returned final score 1(Acceptable) Fig.6(b), and right-side wrist and Forearm score of 2 which brought the final score to 2(Acceptable) Fig.6(c). The dimension of the footrest was increased to 351mm from 313mm to avoid uncomfortable posture by raising the legs while sitting. http://www.iaeme.com/IJMET/index.asp 1021 editor@iaeme.com Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly (a) 95th Percentile (b) RULA Score of Left Side (c) RULA Score of Right Side Figure 7 RULA Analysis with 95th Percentile Manikin 4 DISCUSSION The RULA analysis for 5th, 50th, and 95th percentile Manikins gave the acceptable final score. For three Manikins footrest dimensions varied for a better posture. The results suggest adjustable footrests for broader user groups. Design change in wheelchair legs for adjustable height footrest should undergo Finite Element Analysis as it is the load carrying member. In all analysis, the right-side wrist scored for further investigation. The right-side wrist score of Motorised Wheelchair suggests further design changes for Ergonomic armrest and joystick. Even though the shape of the joystick varies from the normal one, the positions of the buttons and height are same as in standard wheelchairs available in the market. The Ergonomic Wheelchairs for Indian users manufacturer can use the Bobby P Paul et al. (a) Wheelchair Side View (b) Wheelchair Top View (c) Wheelchair Front View Figure 8 Wheelchair Dimensions http://www.iaeme.com/IJMET/index.asp 1022 editor@iaeme.com Bobby P Paul, Darius Gnanaraj S and Sam Paul (a) Motorised Wheelchair (b) Motorised Wheel chair Folded View (c) Foot Rest Folding Fig. 9. Motorised Wheelchair dimensions in Fig.8 to improve the design. Footrest dimensions vary with 5th, 50th, and 95th percentile users as in previous sections. Each part should undergo further Finite Element analysis to determine the thickness. While testing the wheelchair, it was observed that the footrest hits the ground while traveling from inclined to the leveled surface. So, an innovative design of footrest on legs is developed as shown in Fig.9(c) to avoid this problem. The footrest is fixed on the legs itself and can fold before getting on the Wheelchair. 5 CONCLUSION In the paper, a novel design of Foldable Motorised Wheelchair with ladder hinges is discussed. Indian Anthropometric data for Motorised wheelchairs using Human Digital Model is deduced. RULA Analysis is conducted to measure discomforts. An Innovative footrest is developed to avoid footrest hitting the ground while traveling from inclined to leveled ground. ACKNOWLEDGMENTS The authors would like to acknowledge the help of Er. Arun K Varghese Assistant Professor, SAINTGITS College of Engineering, Kottayam, Kerala, Mr Bhargav Sundaram, Chief Executive Officer, Calladi Motor Works, Chennai, Mr Rabindran Isaac, Manager at Samiti for Education, Environment, Social Health Action (SEESHA) Coimbatore, Mr Manjunath Reddy, Mr Ashwin B.N, Mrs Geetha Ashwin, Mr Krishna Kumar for giving us all supports in the design and development of Foldable Motorised Wheelchair for PwD & Elderly. We especially thank Kerala Council for Science Technology and Environment (KSCSTE) for funding this http://www.iaeme.com/IJMET/index.asp 1023 editor@iaeme.com Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly project through the scheme of TECHNOLOGY DEVELOPMENT & ADAPTATION Program (TDAP). 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