PLM Turns Gartner’s Top 5 Smart Factory Risks into Opportunities

Connecting factory and PLM data provides upstream and downstream insights while driving processes automation.

Smart factories are typically defined as paperless, high-tech production facilities that enable real-time collaboration. They are associated with centralized cross-functional operational data, leveraging AI, machine learning and other intelligent systems. However, connecting people and data is also the mantra of product lifecycle management (PLM). The idea here is to ensure that process owners consume the right data at the right time.

Digital transformation seems to be the answer to everything related to product innovation, smart manufacturing and supply chain operations. Additionally, implementing smart factories implies business and digital transformation, needing a shift towards more agility, adaptability and resilience, with the associated cultural alignment needed to successfully adopt new ways of working across the extended enterprise.

The term

The term “smart factory” is widely used in the industry and is recognized by organizations such as the International Electrotechnical Commission (IEC) and the German Federal Ministry for Economic Affairs and Climate Action. (Image courtesy of Bigstock.)

In a recent press release, Gartner highlighted the top five smart factory implementation risks. It read that, “Successful smart factory initiatives require accompanying cultural and operational transformations that are slow by nature and in many cases will require entirely new organizational designs to integrate the new capabilities within the broader supply chain.”

In this post, I discuss how a connected PLM data backbone addresses, links and mitigates these risks.

Gartner Defines Smart Factories and Their Risks

Smart factories are not just about technology adoption, they are about agility, adaptability, actionable data analytics and process integration. As defined by Gartner in its glossary:

“The smart factory is a concept used to describe the application of different combinations of modern technologies to create a hyperflexible, self-adapting manufacturing capability. Smart factories are an opportunity to create new forms of efficiency and flexibility by connecting different processes, information streams and stakeholders (frontline workers, planners, etc.) in a streamlined fashion.”

Smart factories might be referred to as digital or intelligent factories that link smart manufacturing and supply chain operations. When it comes to launching these new initiatives, Gartner identified the following five risks:

  1. Confusing factory optimization with business model transformation.
  2. Overlooking the scope of change management.
  3. Underestimating the complexity of aligning and converging IT, operational technology (OT) and engineering technology (ET).
  4. Insufficient funding for upskilling, reskilling, and talent development.
  5. Narrowly focusing on a single use case and technology.

The Role PLM Plays in Smart Factories

Beyond resource efficiency and process improvement, making factories “smarter” is about business alignment across several PLM perspectives which directly feed into the scope of Industry 4.0. As for what needs to be aligned, that could include everything from product requirements, CAD, software, firmware, BOM data, bills of processes, work instructions, supplier deliverables, product costing, quality and compliance artifacts, material logistics, supply and demand planning and more.

Looking at how smart factories link to the end-to-end PLM data backbone contributes to aligning data assets and insights with business models by:

  • Aligning product development, supplier collaboration and procurement processes—including should-cost assessment.
  • Driving integrated change management between upstream (design office and R&D) and downstream (shop floor, logistics, supply chain, manufacturing engineering) processes.
  • Building the required communication mechanisms, cyber-security, machine interconnections and computing power to process large amounts of data.
  • Monitoring product changes beyond the initial release and into in-field usage and maintenance—enabling rapid issue detection and resolution.
  • Developing or acquiring the required talents, from data scientists to manufacturing engineers and empower them to take appropriate actions.
  • Connecting data threads across PDM, ERP, MES, QMS, LIMS and systems, often beyond the scope of a given factory and expanding across multiple sites and data sources.

Like with any transformations, launching smart factory initiatives requires a mix of digital and business integration. Beyond technical interfaces, this is about business model alignment, from enterprise data collaboration to supply chain operating models. This starts from how OEMs and suppliers exchange data, to how frequently information flows across boundaries—based on the required agility and flexibility.

How PLM Turns Gartner’s Smart Factory Risks into Opportunities

Back to the five top risks identified by Gartner when launching new smart factory initiatives, PLM practices and solutions can help mitigate these by providing a systematic approach to managing product data and processes across the entire product lifecycle. This translates into the following five opportunities:

  1. Providing a holistic view of the product development process, from ideation to end-of-life, and enabling cross-functional collaboration—ensuring that changes made to optimize the factory are aligned with the overall business strategy.
  2. Providing a structured approach to change management, including change request, order, review and approval workflows—ensuring that changes are properly evaluated and approved before and during implementation, improving cross-functional visibility and reducing the risk of unintended consequences.
  3. Providing a centralized platform for managing product data and processes, including integration with other enterprise systems such as ERP, MES and CAD—ensuring that IT, OT and ET systems are properly integrated and aligned.
  4. Providing tools for training and knowledge management, including online training, documentation and collaboration—ensuring that workers have the skills and knowledge needed to effectively use PLM and other enterprise processes and systems.
  5. Providing a flexible platform for managing a wide range of product data and processes, including support for multiple use cases and technologies—ensuring that the scope is not narrowly focused on a single use case or technology, but rather is adaptable to changing business needs and technology trends.

Building the required data backbone to feed and process data from smart factories across to the wider business requires a holistic plan. Furthermore, opportunities include the ability to leverage data visualization technologies (like AR and VR) to assess and interpret functional input into actionable data, and in turn, translate these into cross-functional insights accessible to the wider enterprise.