Understanding Connected Data for Manufacturing
What is connected data?
Today’s manufacturers generate untold megabytes of data every hour of every day. However, most fail to gain anywhere near the value they should be from their data. Data overload and data silos persist. This makes it challenging to establish data relationships and thus extract actionable intelligence. Many manufacturers also miss out on potentially high-value data stranded in today’s smart devices and machines. But connected data technologies—including the latest generation of product lifecycle management (PLM) and Industrial Internet of Things (IIoT) solutions—are changing that dynamic. These solutions enable manufacturers to improve engineering and manufacturing efficiencies, factory performance, reduce costs, speed time-to-market, and increase customer satisfaction.
How does connected data work?
The vision is to create a common data ecosystem that links diverse data assets—both on-premise and in the cloud—and makes it easier to access and validate data, map relationships, and contextualize data (structured, unstructured, and semi-structured) to generate actionable intelligence.
Connected data ecosystems span a variety of data repositories, software applications, and analytical tools. They establish the appropriate data connections, relationships, classifications, and common organizational structures. This results in more accurate, comprehensive, timely, and contextual insights for both human decision support and machine automation. In the best cases, the ecosystem spans the entire digital thread, from engineering to manufacturing and service and ultimately the end customers.
What is an example of connected data technology?
Examples proliferate across all commercial, financial, medical, public utility, and industrial sectors. In the manufacturing space, computer-aided design (CAD), product data management (PDM), Internet of Things (IoT), document management, and other PLM solutions are connecting previously siloed data to create a digital thread between design and engineering, manufacturing and quality control, supply chain, sales and marketing, and customer service organizations. That engineering data should ideally be leveraged to improve manufacturing process down stream with any changes to the original design or work instructions seamlessly leverage into production.
In one example, Fresenius implemented PTC's Windchill PLM solution to move from paper to digital documents to a part-centric approach in its engineering, manufacturing, and customer service functions. The company, a leading global provider of therapeutic services for kidney care, then expanded this solution to encompass system digital twins. This creates a digital thread between engineering, manufacturing, and customer service. The resulting digital intelligence speeds engineering innovation and helps optimize the quality, performance, usability, and uptime of the thousands of Fresenius dialysis machines installed around the world. By monitoring individual patient’s dialysis machines remotely and connecting these data into Windchill, Fresenius can identify the precise makeup of and monitor the performance and usability of each machine. The company has also incorporated mechanisms for nurses and, in some cases, the dialysis patients themselves to provide real-time feedback on usability.
Listen to Matthias Kuss, VP of Data Solutions Fresenius, explain how connected data through Windchill has helped their operations and offerings:
In another manufacturing example, Volvo Construction Equipment established an end-to-end product development process based on connected product data. This creates more efficient ways to work and optimizes both tool chain integration and the user experience. Volvo CE implemented PTC’s Windchill PLM solution to manage its products throughout the entire lifecycle - integrating people, processes, information, and business systems. Volvo also leveraged the ThingWorx Industrial Internet of Things platform (IIoT) to integrate information across multiple software systems (engineering updates from Creo engine computer-aided design (CAD) iterations, downstream Windchill product lifecycle management (PLM) and other manufacturing operations technology and business systems) to enable real-time data synchronicity. The company sought to increase efficiency and quality to improve customer satisfaction with fewer mistakes caused by information handovers.
The results to date have been significant. Volvo CE reports:
- Up to 50% reduction in the number of late loopbacks
- Up to 30% reduction in the cost of poor quality
- Up to 70% efficiency gain from quality of work instructions
- Up to 30% improvement in change management handling
- Up to 40% reduction in duplicate parts
- Up to 30% reduction in poor data entry (due to human errors)
Why is connected data important?
Digital transformation is all about data. But without mechanisms to connect, validate, map relationships, and contextualize data from disparate and often widely dispersed data assets, manufacturing organizations will continue to drown in data, rather than gaining value from it.
Connected data technology will help manufacturers and other organizations tear down existing data silos, automate their operational and business processes, optimize human decision support, and monitor their products from cradle to grave.
What is the future of connected data?
Looking ahead, machine learning, machine reasoning, machine vision, and other artificial intelligence technologies will play an increasingly important role in this space. AI technology will help manufacturers and other organizations acquire, cleanse, aggregate, and transform massive datasets to map critical relationships and distill actionable intelligence from those relationships. At the same time, using connected data to train the AI algorithms will result in more comprehensive models, increasing the accuracy of and thus confidence in those models. Clearly, this is a symbiotic relationship.