AUTONOMOUS SWEEPERS IN MODERN PRODUCTION FACILITIES

whitePaper | February 4, 2022

Digitalization is an evolving process that took roots several decades ago. The first business computers and data storage units emerged in the 1950s. In the 1960s, companies invested in databases and automated processes to make reservations and plan materials or to gain easier access to schedules/inventories, MRP was born in response to the Toyota Production Systems and Methods. In the 1970s, banking experienced its first digital advancement with the invention of ATMs, which ignited a major digitization trend

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 | 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 | March 2, 2020

Discrete manufacturers in Great Britain and around the world have undergone huge transformation in this fourth Industrial Revolution – for a number of reasons. A combination of factors that include economic and market uncertainty, changing customer expectations around technology and a fast-moving green agenda are putting pressure on businesses to hone their supply chains and explore more sustainable and digital business models.

whitePaper | July 13, 2020

There are different tracking technologies typically used in a production facility. Depending on the amount of data transmitted and the complexity of implementation each have corresponding price points. The manual manipulation of hand scanners requires time for processing and allows for error in recording. The cost of implementation is low, but systems require consistent investment of time devoted to ensuring accuracy. The cost to serialize assets for tracking is low, but the data can be damaged and capacity/flexibility for data storage is limited.

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.