DIGITAL TWINS What they are, their value, how they can reduce costs and increase returns in automation

whitePaper | September 4, 2022

It’s the clarion call of today’s marketplace and the prime directive for executives in any business that designs or produces physical goods, no matter how simple or sophisticated. Fortunately, every product can be improved and made at less cost. But how quickly a company can satisfy such demands – before, say, its competitors do, or the market moves on to something new – is largely a function of the product-development cycle. Shorten that cycle, and you can improve the numbers across the board, from customer satisfaction to market share to profitability. However, one seemingly intractable barrier to faster product development lies within the traditional design process. That process starts with identifying a need in the market or within one’s organization; it ends with the manufacture of a finished product, whether a massive, complex assembly or one tiny part. In between are multiple iterations of designs and tests: engineers sketch out a solution, prototype and test it (or run a computerized simulation), and then go back to the design to address any shortcomings. But trade-offs complicate matters each time the cycle repeats: make a part lighter and it’s likely to become weaker, make it stronger and it will probably cost more, and so on. A workable, if not optimal, solution can usually be found. However, finding it often takes longer than the product-development timeline or budget will allow.

whitePaper | April 12, 2023

Industrial companies, such as those in manufacturing, energy, mining, agriculture, and transportation, are increasingly looking to fuel digital transformation—from optimizing operations to accelerating design to reinventing supply chains. For these organizations, data has become the connective tissue that holds their complex industrial systems together.

whitePaper | June 26, 2022

the state-of-the-art procedure and the currently valid standards are presented. Subsequently, existing gaps and possible issues related to additive manufacturing (AM) technology are pointed out. Finally, a feasible procedure is outlined. This first section deals with the process chain and their qualification and validation. Until recently, there was no standard definition of the AM manufacturing process steps. There was a broad consensus to divide the process into pre-, in-, and post-process, but there was no clear division.

whitePaper | May 23, 2022

Cost-effective digital manufacturing solutions are needed to keep factories and supply chains running smoothly while producing high-quality products–whether delivered by OEM, parts or assembly supplier, contract manufacturer, or manufacturing services supplier. IBM can help you cocreate a roadmap to a custom solution with a focus on leveraging existing OT investments,improving key metrics, exploiting digital tools, and using the right talent. We help you set your direction based on a proven Industry 4.0 reference architecture and industry standards, achieve scale by consistently deploying advanced shop floor technologies on an open platform, and unleash optimum value by selecting manufacturingprocess use cases to address immediate needs.

whitePaper | March 16, 2022

What is lights-out warehousing? The simple answer is a facility without people. One that relies entirely on automated equipment, to the point that no manual touches are necessary. With no employees required on the floor, operations do not need to turn the lights on, hence the term “lights-out warehousing.”

whitePaper | January 10, 2023

Now COVID-19 has made it even more pressing to switch to digital, it is high time to say goodbye to manual, paper-based workflows in mass production factories. Digitization is the way forward to Industry 4.0. Because that’s the key to an Overall Equipment Effectiveness (OEE) of world-class level (85%). In reality, most plants today have an OEE closer to 60%. We believe the solution lies in a digital manufacturing platform that supports all plant work processes and utilizes advanced technologies like Machine Learning, IoT, AI and mobile. In this whitepaper, we will show you how such a digital manufacturing platform could work by describing three manufacturing processes: Task Management, Deviation Management and Root Cause Analysis, and how digitalization of these processes can help you achieve an OEE of world-class level.