5 top trends that will drive digital transformation in manufacturing

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A world of interconnected data has changed the way we live and work. Data from connected equipment, lines, processes and facilities is pouring into factories – and the information locked in these data streams has transformed how industrial organizations manage operations, solve issues and adapt to change.

Last year marked a critical inflection point for wide-scale roll out of digital transformation in industrial segments. This year, as companies move into this next phase of digitization and look to benchmark their state of digital operations, keep an eye on these emerging industry trends:

Scale: The magic word for digital transformation in 2020

In 2019, we saw a 400% growth in digital transformation projects moving through the post-implementation stage (per a recent Rockwell study). The maturation of digitization projects will continue throughout 2020, and with this trend, the industry will evolve from exploring the primary benefits of data-driven solutions to understanding how these projects can be used as a resource to help scale smart factory initiatives.

Digital transformation has reached its inflection point. As organizations move their initiatives from project roll-out to continuous process improvement in 2020, scaling becomes a key topic of conversation.

Specifically, the industry will tackle the following challenges as digital business strategies scale and mature:

  • High volumes of industrial infrastructure becoming integrated/connected.
  • Orchestrating multisite roll-outs.
  • Tighter OT/IT integration as more OT infrastructure (devices, production lines, plants) are tied into digital transformation initiatives.

One stop shop: Customers seek single vendor, full-stack solutions to power industrial digital transformation initiatives

Industrial organizations are struggling to effectively deploy and maintain comprehensive, unified digital transformation initiatives – and given the complexity of IIoT systems, customers crave end-to-end partners that can support wide-scale deployments. In fact, 57% of respondents to a recent Rockwell Automation global survey said that having an end-to-end solution provider was extremely important for their digital transformation initiatives.

To experience ROI from digital transformation initiatives, organizations must be able to quickly and efficiently gather enormous quantities of industrial data, include context with the data, and turn it into actionable insights in real-time.

Businesses that are digitally transforming their operations need a complete ecosystem that can help them simplify technology deployments and quickly achieve results. Customers will pursue vendors that provide a single source for services, solutions and updates to the entire IIoT ecosystem - or vendors that leverage partnerships with other vendors to create unified solutions to serve customer needs.

Seamlessly connecting all levels of a business and turning raw data into powerful insights happens when devices and systems are integrated, and data is standardized. However, most vendors can’t do this alone. In 2020, driven by customer demand, more vendors will offer full-stack solutions with the right mix of expertise and technologies to increase digital transformation success and drive project ROI.

The AR workforce arrives: Enabling the “$6 Million Man” of Manufacturing

One of the main concerns for industrial organizations in 2019 was the growing skills shortage and the need for employee cross-training. As a potential solution, employers looked to modernized technology initiatives, such as augmented reality (AR), enabled by digital transformation, to gain an advantage in recruiting, training and employee development.

For example, novice workers can use augmented and mixed reality headsets for training in a digital environment to learn how to handle problems to develop specific skill sets in the industrial environment with high precision and little training before they’re ever exposed to them, such as increased line speed, quality issues, machinery downtime and hazardous conditions.

In previous years, these solutions were still considered mostly hypothetical, yet in 2020, we will see industrial organizations implement fully deployed AR training initiatives.

This shift to “bionic” workers will combine machine and human capabilities to not only increase productivity, tighten production schedules, maximize revenue and protect workers from the injuries associated with repetitive physical tasks, but also develop and enhance human capital from generation to generation via more efficient training.

OT discovery becomes automated

Smart manufacturing requires convergence between IT and OT data to drive visibility, collaboration and efficiency within plants and facilities and across operations. However, two decades after automation networks on the plant floor became ubiquitous, it’s still generally true that information accessibility between plant floor devices (OT) — and the people and systems that can create new value from them (IT) — proves to be a significant challenge.

To remove the complexity and domain expertise required to access plant floor devices and systems, manufacturers are turning to auto-discovery tools that identify assets, collect and integrate data with full OT context, and produce models fully shareable with IT systems. By connecting existing OT infrastructure to smart factory networks and IT initiatives, and continuously generating relevant data insights and measurements, auto-discovery capabilities reduce the technical knowledge and time needed by OT teams to map industrial infrastructure and improve operational efficiency.

Gartner predicts that 50% of OT providers will partner with IT-centric providers for IoT offerings over the next year. Indeed, in 2020, effective OT/IT integration will become key to accelerating innovation and achieving productivity gains at digital transformation scale.

Context is King: The value of OT context becomes clear.

Copious amounts of data is produced on the factory floor every second. However, all this data needs an extra layer to be useful for factory floor operations technology staff: context. By applying context to data pulled from the factory floor, OT teams better understand the insights the data holds and how it impacts the machines and processes they’re responsible for.

On a factory floor, a machine temperature reading without context provides no information to the OT team about the machine approaching a point of overheating, meaning events on that machine need to be redirected. Without context, the value of OT data erodes. Beyond providing continuous insights, the contextual OT data enables IT teams’ digital transformation initiatives across the organization.

In 2020, the value of OT context will drive an increasing demand for interfaces that showcase an analytical combination of OT and IT into a single set of insights. Sharing data models between OT and IT allows users to make actionable, data-driven decisions in real-time. Also, unified visibility into contextualized data will boost workforce productivity, improve the performance of the enterprise, optimizes assets, and execute production with predictability.

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