Other notable\nforecasted statistics sited include: <\/p>\n\n\n\n
- The growth of the smart manufacturing market, which is at $4.4B in 2019, and is expected to increase at a CAGR of 20 percent in the next five years. <\/li>
- The planning investments by manufacturers of 3.24% annually of their revenue in the next three years \u2013 1.7 times more than was invested annually over the past three years. <\/li>
- The building of smart factories increasing by 40 percent in the next five years.
Note:<\/em><\/strong> This is referencing statistics from\u202f<\/em>Capgemini Research Institute<\/em><\/a>\u202freport,\u202f<\/em>Smart Factories @ Scale<\/em><\/a>. <\/em> <\/li><\/ul>\n\n\n\nThe Capgemini\u2019s research identifies two hurdles to establishing\nsmart factory production levels: <\/p>\n\n\n\n
- Converging information technology (IT) and operational technology (OT) systems, <\/li>
- finding job applicants with the proficiency, knowledge and skills to manage smart factories. <\/li><\/ul>\n\n\n\n
This research study surveyed 1,000 manufacturers, concentrating on organizations with a smart factory initiative ongoing. Manufacturers are using practical, proven methods for defining and beginning smart factory ingenuity, depending on reliable systems previously in use by the operations team. <\/p>\n\n\n\n
![\"Bill](\"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2019\/11\/bill-davis.jpg\")
Bill Davis, Director of Industrial Machinery and Heavy Equipment Solutions at Siemens Digital Industries Software<\/em><\/figcaption><\/figure><\/div>\n\n\n\n According to Bill Davis, Director of Industrial Machinery and Heavy\nEquipment Solutions at Siemens Digital Industries Software, \u201c<\/em>a software solution lets you\nsimulate the machine location on the floor and how to get materials to them.\nIt\u2019s process simulation, which is a novel idea to ensure eliminating\nhigh-traffic zones to areas of delay in receiving materials. There\u2019s a need to\noptimize how the work cell is arranged on the shop floor, and in the machine\nbuilder. But, how do you ensure you\u2019re putting the materials needed and defined\nby the manufacturing bill of materials?\u201d<\/em> <\/p>\n\n\n\n
He further describes how materials are arranged on the floor for optimization assembly, as everything needs to be within an arm’s reach, not just the shop layout and simulation, but the process simulation<\/em>. The machinery process is about putting ten pounds of functionality into a five-pound bag. So, it\u2019s a compromise that’s a result of the design; however, the trends are towards adaptability, predictability and extendibility. Therefore, it’s vital to view the human factors for the assembly process and decipher the tools to achieving top quality. <\/p>\n\n\n\n
Emerging technologies increase smart factory implementation <\/h4>\n\n\n\n
\u201cReal-time monitoring is the on-ramp to lights-out manufacturing (or completely automated manufacturing shifts) in plastics and processing industries,\u201d<\/em> says Louis. \u201cManufacturing executives interviewed, see real-time monitoring as providing the contextually rich real-time data stream that enables long-standing technologies like track-and-trace and emerging new technologies (analytics & AI, Industrial IoT, robotics, and smart energy management) to deliver results.\u201d<\/em>\u202f <\/p>\n\n\n\n
Most organizations that we\u2019re preparing to implement smart factory initiatives two years ago have launched them. Isolated manufacturers have the most proactive plans, forecasting 43 percent of all production centers that are converting into smart factories in the next five years. These manufacturers also lead other industries via the adoption index<\/em> through the forecasting period, further emphasizing the active initiatives for competing with smart factories. <\/p>\n\n\n\n
The following core technologies empower smart factories: <\/p>\n\n\n\n
- connectivity<\/em> (leveraging Industrial IoT, collecting data from prevailing equipment and innovative sensors) <\/li>
- intelligent automation<\/em> (advanced robotics, distributed control, drones and machine vision) <\/li>
- cloud-scale data management and analytics<\/em> (implementing predictive analytics and artificial intelligence). <\/li><\/ul>\n\n\n\n
The Capgemini research discovered that new smart factory\nprojects, not based on anything existing, are predominantly rampant among small\nand mid-sized companies below $10B in annual revenue. This category of projects\nembodies 59 percent of the initiatives in 2019 \u2013 an increase of 50 percent to\nthat of reported in 2017.<\/p>\n\n\n\n
According to Davis, skilled worker shortages and\nthe need to rapidly introduce new products are challenging conventional\nmanufacturing approaches. Immersive tools such as augmented reality (AR),\ncombining work instructions, quality checklists with 3D model manipulation and\ntools usage are quickly gaining favor in training new workers for flexible new\nassignments. <\/p>\n\n\n\n
Also, an open infrastructure is incredibly\nhelpful in creating instant dashboards and work tracking for new\nproducts. Historically, a huge up-front effort in data collection and\nprocedures is preceding a product launch. Most of the data collected was\nused initially to refine the process \u2014 never to use again. With smart\ndata collection systems and low code capability to build dashboards, companies\ncan quickly iterate what data is required to ensure the new manufacturing\noperations produce the desired quality. <\/p>\n\n\n\n
Global adoption of smart manufacturing <\/h4>\n\n\n\n
This trend is worldwide, with the top countries for smart manufacturing<\/a> adoption, including the following: <\/p>\n\n\n\n
- China <\/li>
- Germany <\/li>
- Japan <\/li>
- South\nKorea <\/li>
- United\nStates <\/li>
- France <\/li><\/ul>\n\n\n\n
The global surge towards the expansion of smart factories is\nprecipitated by smart manufacturing innovations, which will only continue as\nforecasted with increased competition, propelling it to be a standard in the\nmarketplace. <\/p>\n\n\n\n
\u201cThe\ncost for smart manufacturing implementation is justified by having the world’s\nfastest machines and embracing the digital twin for software development,\nvirtual commissioning and software validation. By leveraging the software from\nan automation perspective, one can validate that the machine is functioning to\nperform the required tasks and increase the speed of the machine due to the\nservo-motor, driving it to greater capabilities,\u201d<\/em> says Bill Davis. <\/p>\n\n\n\n
Global adoption of smart manufacturing\ntechnologies accelerated globally out of necessity for companies to increase\nproduction and address skill set gaps in nearly all industries from retirement.\nMachinery customers, in turn, are demanding smart manufacturing-enabled\nmachines from suppliers. There is a general market demand, but also\nmachine builders are seeing that they can provide differentiation and\ncompetitive advantage by offering turnkey, IoT enabled intelligent machines. It\u2019s\nmore than providing hardware. Tomorrow\u2019s machinery leaders are\nrecognizing that what makes them unique is combining machine operation software\nwith cloud data analytics to mesh seamlessly with their customer\u2019s\nmanufacturing operation. <\/p>\n\n\n\n
One of the terms coined by business consultants\nto describe a strong relationship between a manufacturer and suppliers is\n\u201ccustomer intimacy.\u201d Machinery builders and integrators who can leverage\nthe digital twin of their equipment will be the most successful in creating\ncustomer intimacy, thus retaining a profitable relationship with their customer\nbase. Manufacturing companies are depending more on their machinery\nsuppliers to own the operational risk and smart manufacturing technology,\nleveraging the digital twins in ways for machine builders can succeed. \nFrom simulating the machine or line operation in a customer plant through\nprocess simulation, validating automation code before the machine is assembled,\nmaintaining direct knowledge of the machine conditions for their global\ncustomer base \u2013 all provide tangible, monetary benefit to manufacturing\ncompanies. <\/p>\n\n\n\n
Smart manufacturing initiatives <\/h4>\n\n\n\n
\u201cSmart manufacturing combines business processes, information technology and manufacturing operations optimization with core reliance on a single source of manufacturing truth. So, it\u2019s natural to rely on historical methods for smart factory initiatives,\u201d<\/em> says Davis. Unfortunately, many historical systems are not well integrated between the engineering and manufacturing data sources, and there is nearly always a disconnect. Operations has very good reasons for rearranging and adding to engineering bills of material to align to more efficient operations sequences. Smart manufacturing is about creating efficiency, and a smart factory initiative should take a strong look at how to align engineering and manufacturing in a central source of truth. <\/p>\n\n\n\n
Companies with smart factory initiatives further enforce a where today meets tomorrow<\/em> mindset, while possessing a huge opportunity to invest in automated logistics to the factory floor to increase assembly velocity and decrease work in process inventory. We all know that products are getting more customized and complex, and the work cell or assembly line is getting more crowded and complex. Process simulation is an inexpensive way of gaining new insights into the shop floor and work cell optimization. Manufacturers are becoming more forward thinking about investing in technology such as co-bots, and simulation provides an ideal way to see how complex workflows can be simplified. <\/p>\n\n\n\n
For more information, read Louis Columbus\u2019 full article<\/a> in Forbes.
Related blogs on this topic:
Industrial-machinery and smart manufacturing
<\/a>Implementing smart manufacturing for a smart factory<\/a> <\/p>\n","protected":false},"excerpt":{"rendered":"With the growing trend of additive manufacturing or 3D printing comes the advancement of smart technologies, which further enhances the…<\/p>\n","protected":false},"author":29361,"featured_media":2888,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spanish_translation":"","french_translation":"","german_translation":"","italian_translation":"","polish_translation":"","japanese_translation":"","chinese_translation":"","footnotes":""},"categories":[1],"tags":[],"industry":[145],"product":[],"coauthors":[],"class_list":["post-2887","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","industry-industrial-machinery"],"featured_image_url":"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2020\/01\/smart-manufacturing.jpg","_links":{"self":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/2887","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/users\/29361"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/comments?post=2887"}],"version-history":[{"count":2,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/2887\/revisions"}],"predecessor-version":[{"id":3726,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/2887\/revisions\/3726"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media\/2888"}],"wp:attachment":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media?parent=2887"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/categories?post=2887"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/tags?post=2887"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/industry?post=2887"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/product?post=2887"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/coauthors?post=2887"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
- intelligent automation<\/em> (advanced robotics, distributed control, drones and machine vision) <\/li>
- connectivity<\/em> (leveraging Industrial IoT, collecting data from prevailing equipment and innovative sensors) <\/li>