5 Questions to Ask When Selecting a Process Manufacturing Analytics Solution

September 20, 2017

Process manufacturing organizations run on data-from manufacturing, operations, and business perspective. The data generation and collection strategies at the center of manufacturing processes have evolved dramatically, especially in recent years. Process manufacturers now collect and store huge volumes of data throughout their operations, both on and off premise, across multiple geographic locations, in an increasing number of separate data silos.

Spotlight

Multi-Scale Additive Manufacturing Laboratory

The Multi-Scale Additive Manufacturing Lab focuses on next generation additive manufacturing processes. To this end, the lab explores novel techniques to develop advanced materials, innovative products, modeling and simulation tools, monitoring devices, closed-loop control systems, quality assurance algorithms and holistic in-situ and ex-situ characterization techniques.

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Digital Transformation and Its Impact on Quality Assurance

whitePaper | August 17, 2022

The conversion brought forth by digital transformation and advanced technologies has made a tremendous impact on the way manufacturers process and manage their organizations. While the strategies of agile and modern management systems, specifically quality management, are the result of digital conversion, there is still limited understanding and unclear identification in this new era of quality assurance impact. With the development of digital methodologies, the classical system of operating businesses has been disrupted. As a result, many organizations are in the process of reacting to digitization by utilizing enhanced business platforms and rebuilding the waterfall approach to the agile approach

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4-step holistic manufacturing strategy for the 4th Industrial Revolution

whitePaper | September 30, 2022

Until 2020, progress towards digital transformation for most manufacturers was slow. But the urgency for manufacturers to make successful digital transformations escalated during the first 8-12 months of the global pandemic. As COVID-19 reshaped consumer buying behaviors, the pace jumped from a crawl to a sprint: According to one study, 85% of organizations accelerated their digital transformation initiatives in 2020.[1] Some industry observers believe we witnessed 6.5 years of digital progress in the last eight months of 2020 alone.[2] The pandemic was largely responsible for worldwide supply chain disruptions that slowed down goods production and delivery. As a result, manufacturers justifiably focused on managing and fixing the supply chain problems first. But as the pandemic continued, it became clear that the supply chain issues were a symptom of something deeper than the short-term disruptions.

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Can Industry 4.0 Solve Downtime Issues?

whitePaper | October 3, 2022

If yours is like most businesses today, you run a tight ship. When you see problems on your production line, you do not wait to solve them, and the result is a lean operation that does not let issues linger or snowball into larger problems. But it is impossible to fix what you cannot see or track. While Industry 4.0 is often a buzzword, Watlow® is already providing solutions that are helping manufacturers proactively forecast future issues and reduce costs. Given that the average cost of an hour of downtime in manufacturing was $532,000 in 2021, there is so much opportunity for businesses to save money with Industry 4.0.

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Automation of TS 16949 Processes for Quality Excellence in the Automotive Sector

whitePaper | November 8, 2022

Original Equipment Manufacturers (OEMs), Tier-1 and Tier-2 auto component suppliers and, the entire automotive ecosystem has been investing in R&D and innovation to tap into the opportunity posed by the future of mobility. But the fundamental requirement of quality, cost and delivery hasn’t gone away. By embracing a framework like TS 16949, companies in the automotive sector will be able to embrace Total Quality Management (TQM) requirements, even as they innovate and change at a breakneck pace.

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What Manufacturers Need to Know About Generative Design

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.

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Drive Industry 4.0 results with machine learning

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.

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Spotlight

Multi-Scale Additive Manufacturing Laboratory

The Multi-Scale Additive Manufacturing Lab focuses on next generation additive manufacturing processes. To this end, the lab explores novel techniques to develop advanced materials, innovative products, modeling and simulation tools, monitoring devices, closed-loop control systems, quality assurance algorithms and holistic in-situ and ex-situ characterization techniques.

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