oee.com<\/a>) <\/span><\/p>\nWhy OEE as an important KPI for manufacturing success<\/b><\/h4>\n
OEE<\/strong> is a key KPI for efficiency tracking. The data provides complete details about productivity rate, which in turn helps in reducing downtime, waste etc.\u00c2\u00a0<\/span><\/p>\nWhile we have other KPIs like Overall Operations Effectiveness (OOE), Total Equipment Effective Performance (TEEP), measuring OEE is the most focused and measured KPI because it plays a critical role in identifying root cause issues and accelerating the productivity and RoI. <\/span><\/p>\nOEE benchmarks\u00c2\u00a0<\/b><\/h4>\n
While setting OEE as a KPI for measuring equipment effectiveness is a great move but what do you measure against. You need a baseline right? This is where the OEE benchmark comes in.\u00c2\u00a0<\/span><\/p>\n\n- An OEE score of 100% stands for perfect production.\u00c2\u00a0<\/span><\/li>\n
- An OEE score of 85% is considered as a world-class benchmark for discrete manufacturers with a little room for improvement.\u00c2\u00a0<\/span><\/li>\n
- An OEE score of 60% is for discrete manufacturers means there is some room for improvement.<\/span><\/li>\n
- An OEE score of 40% is quite common among manufacturing companies that just start tracking and improving manufacturing performance. It is a low score and should be addressed quickly.<\/span>\u00c2\u00a0 <\/span><\/li>\n<\/ul>\n
(Source:oee.com)<\/span><\/p>\nHow to calculate OEE and factors contributing to it<\/b><\/h4>\n
As far as OEE is concerned, there are 3 factors that contribute to the OEE data: Availability, Performance and Quality.\u00c2\u00a0<\/span><\/p>\nOEE = Availability x Performance x Quality<\/span><\/strong><\/h5>\nHow to calculate OEE \u00e2€“ includes formula with examples\u00c2\u00a0<\/b><\/h4>\n
Let\u00e2€™s dive deep into each factor in the sections below and let us find out how they are calculated.\u00c2\u00a0\u00c2\u00a0<\/span><\/p>\nWhat is Availability in OEE<\/b><\/h4>\n
It is all about the availability of the machine during a planned schedule. Availability of the machine helps in identifying the losses whenever there is a STOP time or changeover.\u00c2\u00a0<\/span><\/p>\nThe STOP time can be planned or unplanned or changeover, it can impact the availability of the machine leading to produce less than expected.\u00c2\u00a0<\/span><\/p>\nWhile changeovers can\u00e2€™t be eliminated completely, reducing them is always viable to reduce availability loss.\u00c2\u00a0<\/span><\/p>\nAvailability is calculated as shown below.\u00c2\u00a0<\/span><\/p>\n\n- Produced in right time \u00e2€“ availability\u00c2\u00a0<\/span><\/i><\/li>\n<\/ul>\n
Availability (%) = Run Time (operating time) \/Net available time<\/span><\/strong><\/h5>\n*Operating Time = Net Available Time \u00e2€“ Unplanned Downtime<\/span><\/p>\n* Net Available Time = Shift Length \u00e2€“ Planned Downtime<\/span><\/p>\nWhat is Performance in OEE<\/b><\/h4>\n
Performance in OEE provides data on the speed which the machine performs against the desired speed. While the ideal machine running time may be of a certain capacity, real-time running time might be relatively slower.\u00c2\u00a0<\/span><\/p>\nThis can be due to minor stops, idle time or reduced speed.\u00c2\u00a0<\/span><\/p>\nAddressing these challenges will help improve the speed on the work centre and reduce performance loss.\u00c2\u00a0<\/span><\/p>\nThis is how Performance is calculated.\u00c2\u00a0<\/span><\/p>\n\n- Producing product within a stipulated time \u00e2€“ Performance\u00c2\u00a0<\/span><\/li>\n<\/ul>\n
Performance = (Ideal Cycle Time \u00c3— Total Count) \/ Run Time<\/span><\/strong><\/h5>\nWhat is Quality in OEE<\/b><\/h4>\n
Quality in OEE represents the number of goods produced without any defect. If you\u00e2€™ve 100% of goods produced without any defect, then the work centre is performing phenomenally. However, this rarely happens. It is all about reducing the defective products and producing only good quality ones.\u00c2\u00a0<\/span><\/p>\nThis is how Quality is calculated.\u00c2\u00a0<\/span><\/p>\n\n- Produced in right way \u00e2€“ Quality\u00c2\u00a0<\/span><\/li>\n<\/ul>\n
\u00c2\u00a0Quality(%) = (Total Parts Produced \u00e2€“ Total Scrap) \/ Total Parts Produced\u00c2\u00a0<\/span><\/strong><\/h5>\nOEE Calculation Example<\/b><\/h4>\nOEE = Availability x Performance x Quality = 88 x 85 x 97 = 72.5%<\/strong><\/span><\/h5>\nHow to improve OEE Using IoT, mobile app, predictive maintenance\u00c2\u00a0<\/b><\/h3>\nOEE Automation Software<\/b><\/h4>\n
An industrial IoT application coupled with a strong predictive maintenance system can improve overall equipment effectiveness by at least 10x.<\/p>\n
Availability<\/strong> \u00e2€“ Capturing and tracking real-time machine efficiency using IoT (for manufacturing) helps in meeting the targets expected for machines and humans involved in the process.<\/span><\/p>\n
<\/span>\u0627\u0644\u0623\u062f\u0627\u0621<\/strong> \u00e2€“ The IoT data collected from machine and human operations helps identify the frequent downtime and plan for reducing STOP times.\u00c2\u00a0<\/span><\/p>\n\u0627\u0644\u062c\u0648\u062f\u0629<\/i><\/strong> \u00e2€“ Thought Quality can\u00e2€™t be improved directly through such a system, it can be achieved by improving the Availability and Performance of the process.\u00c2\u00a0<\/span><\/p>\nThis is how the system works.<\/span><\/p>\nIoT \u00e2€“ the IoT devices (with sensors) would be fixed on the machines and its real-time downtime and performance under different conditions is captured and pushed to mobile data and to the cloud IoT Platform.\u00c2\u00a0<\/span><\/p>\nThe data captured is then fed into the AI and ML-based predictive maintenance system to predict unplanned downtimes in the future. The entire system provides a massive volume of real-time data that helps in improving the OEE at the work center.\u00c2\u00a0<\/span><\/p>\nEffectiveness vs. efficiency \u00e2€“ What to measure<\/b><\/h4>\n
A short comparison would be:<\/span><\/p>\n\n- Effectiveness \u00e2€“ the rate of what is expected with respect to what is produced\u00c2\u00a0<\/span><\/li>\n
- Efficiency \u00e2€“ Maximum performance of machines under different conditions.\u00c2\u00a0<\/span><\/li>\n<\/ul>\n
The debate between effectiveness and efficiency is always on and many still presume that both mean the same. However, effectiveness is all about how much can be produced with respect to what is expected and depends on required raw materials, machine availability and other resources.\u00c2\u00a0<\/span><\/p>\nOn the other hand, efficiency is all about how much the machine itself can produce to its capacity under different conditions.\u00c2\u00a0<\/span><\/p>\nIn short, a 100% efficient machine is one of the factors that will improve effectiveness on the manufacturing floor.\u00c2\u00a0<\/span><\/p>\nOEE benefits<\/b><\/h3>\n\n- All-in-one metric for measuring manufacturing productivity<\/span><\/li>\n
- Helps map production efficiency with reporting<\/span><\/li>\n
- Maximize equipment RoI<\/span><\/li>\n
- Improve quality<\/span><\/li>\n<\/ul>\n
Measurement of OEE for a Leading Manufacturing Company<\/h4>\n
Our client is leading Industrial Packaging manufacturer supplies to some of the major oil distributors in the region. One of the key challenges they are facing is they were running additional shifts with overtime to meet the production demands. But the production demands were well within the production capacity of the plant. Identifying the reasons for inefficiency and bringing in transparency to all the stakeholders were the expected output of the projects.\u00c2\u00a0<\/span><\/p>\n<\/span><\/p>\nThe shop floor \u00e2€“ assembly line had seven stages and two variants of the products were produced on any given day. Measuring the productivity at each stage in real-time both machine & labour was the key piece of the puzzle.\u00c2\u00a0<\/span><\/p>\nAdditionally, the machine downtime has to be captured and notified to the shop floor supervisor to act promptly and reduce the impact to ensure operations are back on track. Having real-time machine productivity data enabled the supervisors to rectify the problems instantly rather than waiting for a mishap to happen.\u00c2\u00a0\u00c2\u00a0<\/span><\/p>\nWe implemented the connected factory solution by fixing sensors at each stage to measure the output and detect the downtime of the machines. The sensors are connected to the IoT hub, which in turn sends the data to an \u00e2€œIoT Platform\u00e2€, on top of which an analytics engine was built.\u00c2\u00a0<\/span><\/p>\nWe digitized the shop floor operations management right from operator allocation, product change over to measuring labour & machine productivity (OEE & LE) through Industry 4.0 solution.\u00c2\u00a0<\/span><\/p>\nWith access to data on-the-go (Mobile & Web Dashboards), clients were able to identify the bottlenecks and rectify them to improve productivity by 20%. The transparency was created for shop-floor operators by TV displays in the shop floor which in turn helped in increased productivity.<\/span><\/p>\n![\"\"](\"https:\/\/www.hakunamatatatech.com\/wp-content\/uploads\/2019\/06\/Digital-Transformation-Consultation-1024x291.jpg\" "\\"\\"")
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Is my manufacturing process efficient enough? Is my production quality above par? I know this will be a question lingering in the minds of most manufacturers. Measuring the output always matters.\u00c2\u00a0 The manufacturing industry involves a lot of different processes and this makes it complex to track and improve efficiency.\u00c2\u00a0 This is possible, when you<\/p>","protected":false},"author":1,"featured_media":2102,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[17],"tags":[],"class_list":["post-2101","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-transformation"],"_links":{"self":[{"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/posts\/2101","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/comments?post=2101"}],"version-history":[{"count":0,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/posts\/2101\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/media\/2102"}],"wp:attachment":[{"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/media?parent=2101"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/categories?post=2101"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hudutech.com\/ar\/wp-json\/wp\/v2\/tags?post=2101"}],"curies":[{"name":"\u062f\u0628\u0644\u064a\u0648 \u0628\u064a","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}