{"id":3085,"date":"2020-02-11T12:00:00","date_gmt":"2020-02-11T17:00:00","guid":{"rendered":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/?p=3085"},"modified":"2026-03-26T12:03:09","modified_gmt":"2026-03-26T16:03:09","slug":"accelerating-innovation-in-machine-design-and-manufacturing","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/accelerating-innovation-in-machine-design-and-manufacturing\/","title":{"rendered":"Accelerating Innovation in Machine Design and Manufacturing"},"content":{"rendered":"\n

New technologies are driving accelerated change in machine design, engineering and manufacturing. In particular, the embedding of simulation technologies into the design process has been a significant advancement. Embedding simulation technologies enables us to democratize simulation to allow engineers to perform early refinements on their designs without leaving the design environment (figure 1).<\/p>\n\n\n\n

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Figure 1: Engineers can now leverage simulation technologies in the machine design environment for early refinement and optimization. A functional model provides a common language for mechanical, electrical and automation disciplines to work in parallel. <\/figcaption><\/figure>\n\n\n\n

At the same time, technologies enabling multi-discipline\nsimulation and optimization through iteration have been instrumental in\nassisting engineers in solving increasingly complex machine design challenges. These\ntechnological advances have fueled the development of generative design and\nadditive manufacturing, which are expected to become commonplace in machine\ndesign in the next decade. In the future, it will be crucial to continue to\nremove barriers between disciplines and domains, supporting an open and\ninclusive engineering environment.<\/p>\n\n\n\n

Machines have nearly always been a combination of mixed domains\n\u2014mechanical, fluids, electrical, software and thermal. This scenario seems to\nbe accelerating, as machine designers need to find more creative ways to build\nfaster, more reliable and more flexible machines. Thus far, specialized domain\nexpertise and, especially, software that is purpose-built for each domain have\nbeen inhibitors to collaboration and agile machine development.<\/p>\n\n\n\n

Machine builders that do not take an inclusive approach will\nmiss a huge opportunity to create more innovative and differentiated machines.\nThis approach builds the disruption in the industry. Holistic software\nportfolios, such as Xcelerator from Siemens Digital Industries Software,\nprovide the ability to create a complete, multi-domain digital version of the\nmachine and simulate not only the reaction forces of a single-use case, but the\nentire machine operation cycle, validating the PLC code virtually before\ncommissioning the physical machine. The result is a robust machine design that\nis achievable without physical prototyping. Such a comprehensive digital twin\ncan be the impetus behind significant competitive advantage in time-to-market,\ndevelopment cost and differentiated machine designs.<\/p>\n\n\n\n

Realizing the Potential\nof the IIoT<\/strong><\/p>\n\n\n\n

Other essential innovations revolve around leveraging the industrial IoT (IIoT), artificial intelligence (AI), and machine learning (ML). Many machine designers have been using IIoT and smart sensor technology as a way of monitoring machine operation. Still, the future belongs to companies that can use that same technology to influence the actual machine operation (figure 2). In other words, these companies will find ways to create versatile machines that can gather enough information to be able to adjust their performance during operation.<\/p>\n\n\n\n

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Figure 2: Companies that can leverage machine operation data to improve machine performance will gain significant advantages in the future. <\/figcaption><\/figure>\n\n\n\n

A brief example would be a machine tool programmed to\noptimize speed and feed rates based on understanding the workpiece properties\nand machine loading. Computer-aided manufacturing (CAM) programs specify the\nspindle speed and feed rates based on the materials known to the programmer. Significant\nadvancements have been made in CAM technology to eliminate waste through\nadaptive milling in software, helping the upfront CAM design. However, what if\nthe machine tool had sensors to validate the metrology of the part and could\nadapt the code based on specific inputs from sensors to maximize the quality\nand minimize production time?<\/p>\n\n\n\n

Such changes will also enable economic model variations in\nthe way machinery companies interact with their machines over the service life.\nThe ability to collect operating data and perform code optimization to push\ncontinuous improvements to machines in the field will open new business models\nfor companies to provide production-as-a-service. This process will provide\nincreased revenue over time than the build-and-replace business model. Then,\nthe smart sensors provide feedback on machine health with a richer set of\ninformation, having the ability to adjust performance while simultaneously\nrequesting a specific type of service, such as a bearing replacement. This will\nallow quick and accurate maintenance, bringing machines back online faster and\nreducing costs for the customer.<\/p>\n\n\n\n

Moreover, a closed-loop digital thread from machines in\noperation to the digital twin of either the product or the production planning\nwill allow the customer to make informed decisions in confidence, given the\nability to validate or modify it virtually.<\/p>\n\n\n\n

A Renaissance in\nMachine Design and Manufacturing<\/strong><\/p>\n\n\n\n

Under changing socio-economic circumstances and rapid\nadvancements in technology and user experience, manufacturing is experiencing a\nrenaissance. Typically, manufacturing is more conservative in adopting new\ntechnologies, but an aging workforce and the seismic shift in technology\nadoption by those entering that workforce are forcing more rapid changes.<\/p>\n\n\n\n

Greater complexity in all our products and the greater\navailability of digital information about the machine in production will\nradically change manufacturing in the next decade. Manufacturing employees are\nalready seeing how a more intimate user experience will benefit the company and\nmake their work more rewarding and involved. Collaborative robots are only the\nbeginning of this trend. Autonomous machines that adapt to rapid changes in\nproduction requirements will become more common. Factories will also become\nmore flexible to support the demand for mass customization in consumer products.\nThe old ways of thinking about fixed production units and even current efforts\nin lean manufacturing will seem quaint in the next ten years.<\/p>\n\n\n\n

Machine builders will need to establish a robust digital\nthread, extending from design and engineering to the machine in operation, to prepare\nfor the challenges of tomorrow. Integrated software portfolios, such as\nXcelerator, support these closed-loop flows with solutions that enable\ncollaboration and data integrity between engineering domains and throughout the\nproduct or production lifecycle. The result is a comprehensive digital twin of\nthe machine and production processes that enables early validation and\noptimization and, with the IIoT, optimization based on actual performance data.\nCompanies that can leverage these capabilities today will find themselves in a\nstrong position to thrive as the industry continues to evolve.<\/p>\n","protected":false},"excerpt":{"rendered":"

Embedded multi-discipline simulation, the IIoT and more; this is where machine design and manufacturing meets tomorrow.<\/p>\n","protected":false},"author":31575,"featured_media":3087,"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":[63,1],"tags":[174,92,6,73],"industry":[145,144],"product":[],"coauthors":[],"class_list":["post-3085","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured","category-news","tag-todaymeetstomorrow","tag-industrial-machinery","tag-industrial-machinery-and-heavy-equipment","tag-smart-manufacturing","industry-industrial-machinery","industry-industrial-machinery-heavy-equipment"],"featured_image_url":"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2020\/02\/Industrial-Machine-UI-interface-man-Adobe-208731449-scaled.jpg","_links":{"self":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/3085","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\/31575"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/comments?post=3085"}],"version-history":[{"count":4,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/3085\/revisions"}],"predecessor-version":[{"id":3095,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/3085\/revisions\/3095"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media\/3087"}],"wp:attachment":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media?parent=3085"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/categories?post=3085"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/tags?post=3085"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/industry?post=3085"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/product?post=3085"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/coauthors?post=3085"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}