{"id":4483,"date":"2020-06-05T06:13:20","date_gmt":"2020-06-05T06:13:20","guid":{"rendered":"https:\/\/www.gyanvihar.org\/journals\/?p=4483"},"modified":"2020-06-05T06:13:20","modified_gmt":"2020-06-05T06:13:20","slug":"a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors","status":"publish","type":"post","link":"https:\/\/www.gyanvihar.org\/journals\/a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors\/","title":{"rendered":"A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors"},"content":{"rendered":"<p><strong>A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Sasmita Nayak<sup>*a<\/sup>, Neeraj Kumar <sup>b<\/sup>, B. B. Choudhury <sup>c<\/sup><\/strong><\/p>\n<p><sup>*a<\/sup>Ph.D Scholar, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India, Email: sasmitacet@rediffmail.com<\/p>\n<p><sup>b <\/sup>Department of Mechanical Engineering, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India,<\/p>\n<p>Email: neeraj.kumar@mygyanvihar.com<\/p>\n<p><sup>c <\/sup>Department of Mechanical Engineering, Indira Gandhi Institute of Technology (IGIT), Odisha, India, Email: bbcigit@gmail.com<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Abstract <\/strong><\/p>\n<p>&nbsp;<\/p>\n<p>A speedy increase in industrial robots and its usage by different manufacturing industries in a lot many diverse applications is a serious task for the selection of robots. As a consequence, the selection process of the robot becomes incredibly complex for the potential users because they have a large set of attributes and parameters of the robots are available at their disposal. It is a truth that sensible options are higher acquired when theoretical modeling of the hassle is strengthened via experience. The longer the experience, the higher the result we get. The existing work objectives at growing an approach for the choice of robots for industrial functions the place the expertise about the structure, the situation, historical\u00a0 instances of comparable natural surroundings are viewed aside from the robot\u2019s facts and undertaking necessity.<\/p>\n<p><strong>Keywords<\/strong><strong>:<\/strong> Industrial robot, Robot attribute, Robot selection<\/p>\n<p>&nbsp;<\/p>\n<ol>\n<li><strong> Introduction <\/strong><\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>To mark the industrial robot implementation method effective, robot selection essential to approximate successfully and in a systematic process. The performance of a robotic utilization system is the best technique that affects not only the robot, but also the tasks, the complete structure, and the situation. Application of industrial robots is motivated by various technical and economic reasons for increasing the quality of finished products, thin out the waste, raise the level of uniformity of quality, increase the degree of operating safety, etc. The mastery of a robot is very complex in varying operational conditions like the manufacturing environment. In new trend research work robots is the main device in a variety of advanced engineering facilities. The manufacturers developed new kind robots. So, it is a difficult task for the industry to find out a suitable robot from the huse specifications of robots. Various considerations such as availability, production systems, and economics need to be considered. Moreover, many of the attributes are different and contain different units. However, none of these explanations may take care of all the loads and limitations of exact applications.<\/p>\n<p>&nbsp;<\/p>\n<ol start=\"2\">\n<li><strong> Literature review<\/strong><\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>The implementation of industrial robots is typically recognized via making use of many parameters that are necessary and additionally that are realistic parameters[1].\u00a0 i.e repeatability, precision, load size, and speed. \u00a0Repeatability, precision, load size, and speed. Production company requirements aimed at evaluating these parameters are now thoroughly recognized on behalf of evaluated new techniques for examining robotic implementation growth[2]. A big quantity of attributes is used for leveling and the decision of industrial robots with the assist of TOPSIS and graphical techniques[3] which evaluating the leveling assumed via these techniques. Still, the loads given by way of the authors to the parameters had been now not steady. Khouja and kumar[4] proposed the options theory and funding assessment system aimed at the preference of robots. A funding comparison for the use of information envelopment evaluation for robotic decision is carried out[5]. A selection aid machine[6] primarily built on analytical algorithms to choose operating facilities of best in the market environment.<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<ol start=\"3\">\n<li><strong> Proposed Methodology for the selection of an industrial robot.<\/strong><\/li>\n<\/ol>\n<p>Similarity opinion is a more important component of the \u201cexperts\u201d perception which requires for well informed regain. According to parliamentary law which embraces a concept of similarity, the given below presumptions is realized:<\/p>\n<ul>\n<li>The excessive resemblance among the query issue and the confirmed case stands due to excessive possible for answering the difficulty.<\/li>\n<li>Resemblance funds on a previous experience with records, which offers a quantitative value.<\/li>\n<li>A similar question has resembled<\/li>\n<li>The regain event is helpful if it is a resemblance to a query issue<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>According to this written report, frequent strategies usage of computable resemblance cost for the regain of valuable activities are realized using spontaneous select a parameter and searching at its matching\/resemblance listing regarding the undertaking of its environment.<br \/>\nAn\u00a0established\u00a0case (Case = Problem + Solution) units of facts existence, which shops the preceding ride of robotic choice. The usual facts existence includes the robotic description and methods of organizing a possible plan for the robotic determination of graph and distance designing. All steps are explained below,<br \/>\n\u2022Pick-up subsequent and observe the equal process<br \/>\n\u2022 Extend the equal\u00a0operation by accessible\u00a0rebates<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<ol start=\"4\">\n<li><strong>Proposed workflow for selection of robot rank <\/strong><\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>The proposed robot selection procedure follows the main five more important tasks which are given below:<\/p>\n<p>&nbsp;<\/p>\n<ol>\n<li>Information database \u2013 start ruling new approach, technique execution, technique demands, and justification.<\/li>\n<li>Indexing \u2013 understand\u00a0attributes, take a look at the assist\u00a0of similarity case.<\/li>\n<li>Initial answer\u00a0\u2013\u00a0select nearly\u00a0all\u00a0comparable\u00a0and potential robotic\u00a0use cases.<\/li>\n<li>Iteration \u2013regulate options\u00a0to\u00a0appropriatethe ongoing robotic decision\u00a0query.<\/li>\n<li>Implementation-\u00a0follow\u00a0work cell design,\u00a0price estimate, plan\u00a0analysis.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>The continual-base similarity calculation with the attributes alike\u00a0value\u00a0differentiation, price, etc. is\u00a0proven\u00a0in Figure 1.<\/p>\n<p><strong><br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-4484\" src=\"https:\/\/www.gyanvihar.org\/journals\/wp-content\/uploads\/2020\/06\/P1.png\" alt=\"\" width=\"1366\" height=\"768\" srcset=\"https:\/\/www.gyanvihar.org\/journals\/uploads\/2020\/06\/P1.png 1366w, https:\/\/www.gyanvihar.org\/journals\/uploads\/2020\/06\/P1-768x432.png 768w, https:\/\/www.gyanvihar.org\/journals\/uploads\/2020\/06\/P1-1024x576.png 1024w, https:\/\/www.gyanvihar.org\/journals\/uploads\/2020\/06\/P1-624x351.png 624w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/>\u00a0<\/strong><\/p>\n<p><strong>Figure 1. Robot selection process architecture<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Table 1. parameter values of different robots<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<table width=\"0\">\n<tbody>\n<tr>\n<td width=\"104\">Specification<\/td>\n<td width=\"103\">Robot-1<\/td>\n<td width=\"114\">Robot-2<\/td>\n<td width=\"125\">Robot-3<\/td>\n<td width=\"100\">Robot-4<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">&nbsp;<\/td>\n<td width=\"103\">(Puma (560-c)<\/td>\n<td width=\"114\">(Adept one XL)<\/td>\n<td width=\"125\">Fanuc Arcmate<\/p>\n<p>Sr.R.J<\/td>\n<td width=\"100\">Staubli RX<\/p>\n<p>130B<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">DOF<\/td>\n<td width=\"103\">6<\/td>\n<td width=\"114\">3<\/td>\n<td width=\"125\">6<\/td>\n<td width=\"100\">6<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Pay Load<\/td>\n<td width=\"103\">4 kg<\/td>\n<td width=\"114\">3.5 kg<\/td>\n<td width=\"125\">8 kg<\/td>\n<td width=\"100\">\u00a0\u00a0\u00a0\u00a0\u00a0 10 kg<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Swept Area<\/td>\n<td width=\"103\">320<sup>\u00b0<\/sup><\/td>\n<td width=\"114\">260<sup>\u00b0<\/sup><\/td>\n<td width=\"125\">270<sup>\u00b0<\/sup><\/td>\n<td width=\"100\">300<sup>\u00b0<\/sup><\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Max. Reach<\/td>\n<td width=\"103\">878 mm<\/td>\n<td width=\"114\">500 mm<\/td>\n<td width=\"125\">1430 mm<\/td>\n<td width=\"100\">1060 mm<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Max Speed<\/td>\n<td width=\"103\">1.0 m\/sec<\/td>\n<td width=\"114\">0.9 m\/sec<\/td>\n<td width=\"125\">3.65 m\/sec<\/td>\n<td width=\"100\">3.12m \/sec<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Price<\/td>\n<td width=\"103\">$36,000<\/td>\n<td width=\"114\">$19,000<\/td>\n<td width=\"125\">$55,400<\/td>\n<td width=\"100\">$61,000<\/td>\n<\/tr>\n<tr>\n<td width=\"104\">Repeatability<\/td>\n<td width=\"103\">0.1 mm<\/td>\n<td width=\"114\">0.020 mm<\/td>\n<td width=\"125\">0.11 mm<\/td>\n<td width=\"100\">0.03\u00a0\u00a0\u00a0 mm<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>A few similarity dimension techniques are regarded then they have to be served not likely for the similarity calculation. The present-day function in the course of the refinement of a\u00a0determination approach is defined through the record&#8217;s attributes acknowledged spot. The final problem, as its future may additionally seem to be in the case of memory, is a complete set of illuminating characteristics. The gathered records\u00a0attribute results\u00a0from the actual implementation case study. The geometry\u00a0price\u00a0of\u00a0distinct instances\u00a0of the\u00a0robotic is given in Table 1. Table2. Register\u00a0question trouble\u00a0and\u00a0validated\u00a0the case for palletizing\u00a0robotic\u00a0selection. Unlikely attributes have\u00a0distinct significance\u00a0(loads). The following weights are\u00a0viewed\u00a0for the similarity calculation:<\/p>\n<ul>\n<li>Really very\u00a0important= 13\u00a0(Ex. Manipulator reach);<\/li>\n<li>Very important = 9 (Ex: price range);<\/li>\n<li>More important = 5 (Ex: Repeatability,Payload, etc); and<\/li>\n<li>Important = 4 (Ex: Swept area)<\/li>\n<li>Somewhat important=2(Ex: Maximum end effector speed)<\/li>\n<li>Less important = 1 (Ex: Degree of freedom)<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>For uncomplicated reference, all useful notations for our model are summarized in Table 3.<\/p>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"55\">Sl. No.<\/td>\n<td width=\"114\">Operation features<\/td>\n<td width=\"84\">Information<\/td>\n<td width=\"54\">Weight<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">1<\/td>\n<td width=\"114\">Price range<\/td>\n<td width=\"84\">$ 19500<\/td>\n<td width=\"54\">9<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">2<\/td>\n<td width=\"114\">Pick up range<\/td>\n<td width=\"84\">55deg\/sec<\/td>\n<td width=\"54\">4<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">3<\/td>\n<td width=\"114\">Manipulator Reach<\/td>\n<td width=\"84\">800mm<\/td>\n<td width=\"54\">13<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">4<\/td>\n<td width=\"114\">load<\/td>\n<td width=\"84\">5kg<\/td>\n<td width=\"54\">5<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">5<\/td>\n<td width=\"114\">Velocity<\/td>\n<td width=\"84\">1.1m\/sec<\/td>\n<td width=\"54\">2<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">6<\/td>\n<td width=\"114\">Repeatability<\/td>\n<td width=\"84\">\u00b10.2mm<\/td>\n<td width=\"54\">5<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">7<\/td>\n<td width=\"114\">Degree of freedom<\/td>\n<td width=\"84\">2<\/td>\n<td width=\"54\">1<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">8<\/td>\n<td width=\"114\">Types of actuators<\/td>\n<td width=\"84\">&nbsp;<\/td>\n<td width=\"54\">0<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">9<\/td>\n<td width=\"114\">Programming method<\/td>\n<td width=\"84\">&nbsp;<\/td>\n<td width=\"54\">0<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">10<\/td>\n<td width=\"114\">Downtime<\/td>\n<td width=\"84\">&nbsp;<\/td>\n<td width=\"54\">0<\/td>\n<\/tr>\n<tr>\n<td width=\"55\">11<\/td>\n<td width=\"114\">Reliability<\/td>\n<td width=\"84\">&nbsp;<\/td>\n<td width=\"54\">0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Table 2. A basic case (Query problem)<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Table 3. \u00a0Notation for case<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"76\">Notations<\/td>\n<td width=\"197\">Definition<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>C\u2019<\/em><\/td>\n<td width=\"197\">Confirmed instance<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>i<\/em><\/td>\n<td width=\"197\">Number of cases<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>Q<\/em><\/td>\n<td width=\"197\">Query instance<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>I <\/em><\/td>\n<td width=\"197\">Factor index set, I = {1, 2, &#8230;, n}<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>n<\/em><\/td>\n<td width=\"197\">Factors figure to be nominated<\/td>\n<\/tr>\n<tr>\n<td width=\"76\">S\u2019<\/td>\n<td width=\"197\">Similarity instance<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>J<\/em><\/td>\n<td width=\"197\">Cause table set,J={ 1,2,\u2026,n}<\/td>\n<\/tr>\n<tr>\n<td width=\"76\"><em>M<\/em><\/td>\n<td width=\"197\">load<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Table 4. Similarity computation example -1<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"101\">Features<\/td>\n<td width=\"78\">Query Case<\/td>\n<td width=\"72\">Similarity<\/td>\n<td width=\"74\">Confirmed Case 1<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">cost<\/td>\n<td width=\"78\">$19,000<\/td>\n<td width=\"72\">0.528<\/td>\n<td width=\"74\">$36000<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Swept area<\/td>\n<td width=\"78\">260<sup>\u00b0<\/sup><\/td>\n<td width=\"72\">0.812<\/td>\n<td width=\"74\">\u00a0 320<sup>\u00b0<\/sup><\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Repeatability<\/td>\n<td width=\"78\">0.020mm<\/td>\n<td width=\"72\">0.2<\/td>\n<td width=\"74\">0.1 mm<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Max. Reach<\/td>\n<td width=\"78\">500 mm<\/td>\n<td width=\"72\">0.569<\/td>\n<td width=\"74\">878 mm<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Payload<\/td>\n<td width=\"78\">3.5 kg<\/td>\n<td width=\"72\">0.875<\/td>\n<td width=\"74\">4 kg<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Max Speed<\/td>\n<td width=\"78\">0.9 m\/sec<\/td>\n<td width=\"72\">0.9<\/td>\n<td width=\"74\">1.0 m\/sec<\/td>\n<\/tr>\n<tr>\n<td width=\"101\">Degrees of freedom<\/td>\n<td width=\"78\">3<\/td>\n<td width=\"72\">0.5<\/td>\n<td width=\"74\">6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>Similarity of singular features<\/p>\n<p>Similarity query case=<\/p>\n<p>Similarity (Case 1) = 1\/39 [9 \u00b4 0.528 + 4\u00b40.812 + 1 \u00b40.2 + 13\u00b40.569 + 5\u00b4 0.875 +2 \u00b40.9+ 1 \u00b4 0.5] = 22.272\/39 = 0.571<\/p>\n<p>Similarity (Case 2) = 1\/39 [9 \u00b4 0.974 + 4\u00b40.962 + 1 \u00b40.8 + 13\u00b40.625 + 5\u00b4 0.291 +2 \u00b40.75+ 1 \u00b4 0.75] = 25.244\/39 = 0.647<\/p>\n<p>Similarity (Case 3) = 1\/39 [9 \u00b4 0.343 + 4\u00b40.866 + 1 \u00b40.181 + 13\u00b40.327 + 5\u00b4 0.35 +2 \u00b40.25+ 1 \u00b4 0.5] = 13.733\/39 = 0.352<\/p>\n<p>Similarity (Case 4) = 1\/39 [9 \u00b4 0.311 + 4\u00b40.812 + 1 \u00b40.666 + 13\u00b40.4 + 5\u00b4 0.291 +2 \u00b40.291+ 1 \u00b4 0.5]= 14.45\/39 = 0.370<\/p>\n<p>&nbsp;<\/p>\n<ol start=\"4\">\n<li><strong> RESULTS AND CONCLUSION<\/strong><\/li>\n<\/ol>\n<p>The robots are ranked by the liking primarily based on the precise points\u00a0chosen to hold the purposive use in view. Granting to the outcomes\u00a0of the instance\u00a0problem, Fanuc Arcmate Sr.R.J that has the easiest\u00a0utilization fee ought to be\u00a0mentioned as the pleasant robotic\u00a0substitute. The 1st ranked robotic\u00a0has the most cost of DOF, price, load, and swept region\u00a0the\u00a0first-rate repeatability data amongst all the golems. The 2nd ranked robot\u00a0has the\u00a0best\u00a0cost,\u00a0however\u00a0the lowest swept area, max. Reach and repeatability with the very best payload\u00a0capability\u00a0in\u00a0comparison\u00a0to 1st ranked robot. In parliamentary\u00a0regulation to separate between these two\u00a0robotic\u00a0alternatives, the utilization\u00a0ranking has to\u00a0be\u00a0regarded. A\u00a0 robotic choice\u00a0with extraordinarily excessive utilization is greater workable\u00a0to\u00a0exhibit higher performance. In the\u00a0facts set, P, G, and VG denote poor, good, and very\u00a0accurate respectively (Table 5).<\/p>\n<p><strong>Table 5.selection of the robot.<\/strong><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td width=\"46\"><strong>Sl.no.<\/strong><\/td>\n<td width=\"57\"><strong>Robots<\/strong><\/td>\n<td width=\"72\"><strong>Similarity (Relative closeness)<\/strong><\/td>\n<td width=\"63\"><strong>Ranking<\/strong><\/td>\n<td width=\"75\"><strong>Rating<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"46\">1<\/td>\n<td width=\"57\">Robot-1<\/td>\n<td width=\"72\">0.571<\/td>\n<td width=\"63\">3<\/td>\n<td width=\"75\">Very good<\/td>\n<\/tr>\n<tr>\n<td width=\"46\">2<\/td>\n<td width=\"57\">Robot-2<\/td>\n<td width=\"72\">0.647<\/td>\n<td width=\"63\">4<\/td>\n<td width=\"75\">Poor<\/td>\n<\/tr>\n<tr>\n<td width=\"46\">3<\/td>\n<td width=\"57\">Robot-3<\/td>\n<td width=\"72\">0.352<\/td>\n<td width=\"63\">1<\/td>\n<td width=\"75\">Very good<\/td>\n<\/tr>\n<tr>\n<td width=\"46\">4<\/td>\n<td width=\"57\">Robot-4<\/td>\n<td width=\"72\">0.370<\/td>\n<td width=\"63\">2<\/td>\n<td width=\"75\">Good<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-4485\" src=\"https:\/\/www.gyanvihar.org\/journals\/wp-content\/uploads\/2020\/06\/P2.png\" alt=\"\" width=\"305\" height=\"317\" \/><\/p>\n<p><strong>Figure 2. Utilization of Robots<\/strong><\/p>\n<p>In parliamentary law to specify that the closeness factor plays an important role in finding the ranks of robots. the order of predilection of the robot alternatives about the closeness or similarity increase in amount principle, a ranking process turn into important. The proper utilization of Robots is presented in Figure 2. The advised technique is general for finding out an effective and efficient robot selection methodology.<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<ol start=\"5\">\n<li><strong> CONCLUSION<\/strong><\/li>\n<\/ol>\n<p>The case-based approach for the selection of an industrial robot is studied and the result analysis is successfully performed. It is found that the similarity case-based method gives a good resolution with very little error. The composition gives a methodology for the intention of simplification, between two cases based on the weighted aggregate of local similarity of all the robot features suggest computing the global similarity which helps in the choice of a suitable robot from among a large number of available alternatives robots.<\/p>\n<p>Nevertheless, earlier than\u00a0a conclusion is assumed, the factors\u00a0such as financial\u00a0reflections, accessibility, administration\u00a0limitations, and\u00a0global market policies, etc.\u00a0may also\u00a0be viewed. In the modern job, 15aspects\u00a0of the robots are\u00a0diagnosed\u00a0and the weight has been given to most of the robotic\u00a0attributes, which will restore\u00a0the robotic precisely\u00a0and correctly. The weight\u00a0aspect\u00a0coding scheme is explained with examples. The approach established\u00a0through this employment would\u00a0assist manufacturing engineers to\u00a0pick\u00a0robots for computerized work\u00a0cell\u00a0plan. Hence, the similarity case-based\u00a0technique offers higher decision with much less\u00a0time-consuming\u00a0technique\u00a0than\u00a0different easiest\u00a0method.<\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p><strong>Reference <\/strong><\/p>\n<p>[1] A. Seidmann, A. Arbel, and R.Shapira, A two-phase analytic approach to robotic system design, Robotics and Computer-Integrated Manufacturing, 12, pp.181-190, 1984.<\/p>\n<p>[2] O. F. Offodile, and K. PO.Ugwu, Evaluating the effect of speed and payload on robot repeatability, International Journal of Robotics and Computer Integrated Manufacturing, 8, pp.27-33, 1991.<\/p>\n<p>[3] P.P.Bhangale, V.P.Agrawal, and S.K.Saha, Attribute based specification, comparison and selection of a robot, Mechanism &amp; Machine Theory 39, pp.1345-1366, 2004.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>[4] M.J.Khouja and R.L.Kumar, An options view of robot performance parameters in a dynamic environment, International Journal of Production Research, 37, pp.1243-1257, 1999.<\/p>\n<p>[5] M.Bragilia and A. Petroni, Evaluating and selecting investments in industrial robots, International Journal of Production Research, 37, pp. 4157-4178,1999.<\/p>\n<p>[6] A.M.Layek and L.J.Resare, Algorithm based decision support system for the concerted selection of equipment in machining\/assembly cells, International Journal of Production Research, 38, pp.323\u2013339, 2000.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><a href=\"https:\/\/www.gyanvihar.org\/journals\/wp-content\/uploads\/2020\/06\/Sasmita-Nayak_CaseBaseApproach_06-05-2020.pdf\">Sasmita Nayak_CaseBaseApproach_06-05-2020<\/a><\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<h1><\/h1>\n","protected":false},"excerpt":{"rendered":"<p>A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors \u00a0 Sasmita Nayak*a, Neeraj Kumar b, B. B. Choudhury c *aPh.D Scholar, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India, Email: sasmitacet@rediffmail.com b Department of Mechanical Engineering, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India, Email: neeraj.kumar@mygyanvihar.com c Department of Mechanical Engineering, Indira [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[120],"tags":[],"class_list":["post-4483","post","type-post","status-publish","format-standard","hentry","category-volume-6-issue-1-2020"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>research journal - Research Journal<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.gyanvihar.org\/journals\/a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors - research journal\" \/>\n<meta property=\"og:description\" content=\"A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors \u00a0 Sasmita Nayak*a, Neeraj Kumar b, B. 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Choudhury c *aPh.D Scholar, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India, Email: sasmitacet@rediffmail.com b Department of Mechanical Engineering, Suresh Gyan Vihar University (SGVU), Jaipur, Rajasthan, India, Email: neeraj.kumar@mygyanvihar.com c Department of Mechanical Engineering, Indira [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.gyanvihar.org\/journals\/a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors\/\" \/>\n<meta property=\"og:site_name\" content=\"research journal\" \/>\n<meta property=\"article:published_time\" content=\"2020-06-05T06:13:20+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.gyanvihar.org\/journals\/uploads\/2020\/06\/P1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1366\" \/>\n\t<meta property=\"og:image:height\" content=\"768\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"gyanvihar3\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"gyanvihar3\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.gyanvihar.org\/journals\/a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors\/\",\"url\":\"https:\/\/www.gyanvihar.org\/journals\/a-case-based-approach-for-the-selection-of-industrial-robots-in-manufacturing-sectors\/\",\"name\":\"A Case-Based Approach for the Selection of Industrial Robots in Manufacturing Sectors - 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