Digital continuity: As factories implement smart technologies, consistent data becomes vital

Whether they call it Industry 4.0 or “smart” manufacturing, experts worldwide are focused on how to extract data from intelligent machines and then analyse it to improve both their products and the processes used to create them.

Benefits include improved efficiencies and reduced costs, plus the ability to quickly respond to market trends with personalised solutions.

In the race to Industry 4.0, many manufacturers are tripping over data silos. Although state-of-the art when installed, data in any of these ageing legacy systems must typically be re-created in one or more of the downstream systems.

The resulting duplication and inconsistency make it impossible to analyse data for insights and contributes significantly to the inefficiencies found in manufacturing today.

The antidote is “digital continuity,” a concept that is increasingly critical as auto manufacturers juggle a ballooning product set driven by rapidly evolving ownership models, fuel sources and degrees of driver autonomy.

“Digital continuity is the core characteristic that we need for the 21st century digital world,” said Michael Grieves, executive director for the Centre for Advanced Manufacturing and Innovative Design at the Florida Institute of Technology.

“We cannot afford to not know that the version of design we are using has been obsoleted by a newer design. We cannot afford to have Engineering send designs to Manufacturing that Manufacturing knows cannot be built properly or cost effectively. We cannot afford to not know what machine-to-machine communications are occurring that will result in a major manufacturing failure.”

Siloed data complicates industrial value chain

Manufacturers of all types recognise the challenge, according to LNS Research, a Massachusetts-based business consultancy focused on digital transformation. In a 2015 study –The Global State of Manufacturing Operations Management Software: Weaving the Digital Thread Across Industrial Value Chains, LNS surveyed discrete and process manufacturers of all sizes in North America, Europe and Asia-Pacific.

The study found that the top two operational challenges respondents cited were directly related to a failure of digital continuity: a lack of collaboration across departments (48%); and disparate systems and data sources (39%).

Nearly as many – 38% each – cited difficulty coordinating across their supply and demand chains, a lack of timely visibility in manufacturing performance metrics and a lack of continuous improvement culture/ processes. (Due to multiple responses, the total is more than 100%.) Digital continuity could help to address them all.

“With an unbroken flow of information,” LNS concluded, “decisions stemming from any part of operations, such as quality issues, asset management, meeting supply, customer sentiments and others, can be accessed and integrated to specific decisions among those respective departments and companies, leading to overall increases in productivity, quality, profit and other key performance indicators.”

Do you know what I want?

Digital continuity creates a unique, authoritative and consistent source of data across the entire lifecycle as a product moves from concept to design, engineering, manufacturing and post-sales service.

“The idea behind digital continuity is that, while we still have a progression in time from product creation to product operation and support, the information in these phases is integrated within the other phases,” Grieves said.

“In the product creation phase, for example, not only is the product engineered to meet its functional requirements, but the product is also designed for manufacturability and supportability. Information about actual manufacturability is fed back into the engineering phase in order to address potential future manufacturability issues.

“Information about the actual performance of the product is fed back to engineering and to manufacturing, so that improvements to the product and its manufacturability can be assessed.”

Pairing real-world data with scientifically accurate 3D models of the product and the factory allows manufacturers to monitor the real-time environment and predict its future state, Grieves said. By simulating the factory’s operations minutes or hours in advance, plant managers can detect and correct issues before they happen, balance work cells, implement process quality enhancements and improve worker safety.

Don’t wait for a big bang answer

Fortunately, the challenge of achieving digital continuity is being made easier by the same technologies driving digital transformation. These technologies also eliminate the risk factor because they work with the legacy systems automakers have already installed.

Sophisticated digital platforms, for example, are now equipped with powerful search engines that can tap both structured and unstructured information stored in existing legacy systems. The platforms scour all of a company’s systems for relevant information, then compile and present it to users as data and predictive analytics.

Every authorised user, whether they sit inside the OEM or work for a supply chain partner, sees the same data, formatted for each person’s specific function. As changes are made downstream, the data presented to all users update continuously, ensuring accuracy and timeliness.

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