How to address digital transformation challenges

Digital transformation of manufacturing has been a leading topic of discussion within industry for decades. The reality is the push to advanced technology in manufacturing industries has been going on for a very long time, with the first programmable logic controller (PLC) introduced nearly 50 years ago, and the first distributed control system (DCS) following about 5 years later.

Back then, the idea of replacing pneumatic controls, relays and loop controllers with solid-state automation systems able to perform consistently and flawlessly was a major step forward, and it laid the foundation for many subsequent technologies. Today, while industrial plants and facilities still make extensive use of traditional automation, most related technologies, including PLCs and DCS, have advanced substantially in terms of functionality and interoperability.

The plant floor now includes smart devices communicating over high-speed networks to deliver a wealth of data beyond process variables and status. For example, diagnostics data is available for instruments, as well as for the machines and process units they monitor. Using this and other new data sources, worker safety and plant availability have been dramatically improved, while plant efficiency has increased at an even higher rate.

Automation systems initially emphasized monitoring and control, but they also could track and maintain history. This historical data was transformed into displays and reports, enabling a view into the plant not previously available. Ultimately, this information was made available to systems operating at enterprise levels, creating additional opportunities for operational improvements.

If digital transformation began in the 1970s and plants have incorporated many of the associated technologies, why are we still talking about it today? Clearly, the advances we made in the process and discrete industries have produced unprecedented improvements. Manufacturing costs have been greatly reduced as yields have increased and as the labor content per unit has decreased. However, due to numerous challenges, our ability to apply all this data and information to fully use its power has not kept pace with the technologies now available in modern devices and systems.

Raw data into actionable information

Replacement of manual, pneumatic and relay control with intelligent automation systems is relatively straightforward. Documenting the necessary control functions and configuring/programming the automation elements typically is not complicated and results in substantial improvements.

But today, manufacturers need to derive higher degrees of benefit from the vast amount of collected data to unlock even greater value within operations. This digital transformation will require improved strategies to make the best use of resources within the company — and may even necessitate tapping into the abilities of business partners. The opportunity to transform business is there, but it can be intimidating as key questions must first be answered, including:

• Where do I start?
• How much will it cost?
• Can I build a business case?
• If I make the investment, can our company handle the change?

These questions become even more challenging because digital transformation is different for every company. Enterprises each have a different starting point, vision and definition of success. Operations leaders must clearly communicate to their organization what they intend to derive from digital transformation (see Figure 1).

In other words, digital transformation leaders must create an organization where operations are integrated so key strategies can be deployed, lessons learned can be applied throughout the company and operations can be harmonized. A combination of investments in technology and people is typically required to reach these goals, as detailed in the following examples.

Bottom-up instead of top-down

This company has a traditional corporate structure, with centralized personnel overseeing many operating business units, each of which performs various functions, including manufacturing (see Figure 2).

Figure 3: Edicts issued at the corporate level won’t be effective without buy-in from each business unit. Courtesy: Emerson[/caption]

Plant personnel progressively and continuously look for improvement opportunities. The actions they undertake do not depend on a corporate directive but are instead based on known needs for improving operations. Plant personnel constantly lean out operations by devising mechanical and software tools to improve productivity and reduce cost. This bottom-up approach ensures effectiveness because each proposed change is suggested by those closest to the problem, enabling rapid recognition followed by quick solution implementations.

Admittedly, execution of this strategy is simplified because there is only one site for high-volume manufacturing, and it is co-located with headquarters, but the basic concept is applicable to any company. The main challenge for businesses with multiple large manufacturing centers is ensuring that as new tools and practices are developed, they are documented and shared such that each site runs similar procedures.

When manufacturing is more distributed, challenges are created in terms of sharing innovation, which requires rapid coordination for deployment at other sites. Cooperation with corporate management also can be more difficult, but modern communication technologies can address many of these issues.

Put people first

One of Emerson Machine Automation’s customers runs a pulp and paper plant making multiple products including sandwich wrappers and cardboard, and they are betting big on the rapid adoption of paper straws. The plant has four different PLC platforms and three different DCS.

Figure 5: Manufacturers are just beginning to effectively use existing big data to improve operations. Courtesy: Emerson[/caption]

The plant has the intelligent devices and platforms required to provide the foundational data needed to achieve top quartile performance, but it doesn’t have easy access to the data. For this company, installing a new control room is a great first step on the road to implementing a full-blown industrial internet of things (IIoT) strategy by making more data available to the entire team.

This paper plant is no different from most, as most plants use little of the available data. The 5% estimate called out in Figure 5 is quite conservative, as many estimate slightly more than 1% of the available data is actually used to improve operations.

Looking ahead

These are two examples of the challenges facing companies today. Others arise as companies grow and expand IT systems, and as acquisitions introduce new IT and automation systems. The business environment, regulatory controls and laws change, requiring manufacturing to respond. But a truly connected enterprise will be adaptable and agile, allowing it to keep abreast of changes in the operating environment.

Superior digital transformation requires both technical and personnel improvement. Productivity gains from automation are frequently negatively impacted by lack of preparation of operational staff due to insufficient training or mismatched skill sets. But even with these and other challenges, an overwhelming majority of companies believe intelligent implementation of an IIoT strategy is crucial to their continued success.

In the automation world, digital transformation is often viewed in terms of improving manufacturing efficiency. Historical information is digested to improve prediction, and analytics are added to improve understanding of current conditions and needed changes. A need also arises to increase the speed at which decisions are made, all with the intent of creating more efficient operations. Along with these challenges, as the world becomes more data-driven, automation systems must be integrated with IT infrastructure and policies.

While digital transformation as described above can be complicated, manufacturers still need to drive forward, or risk being left behind. While each company faces different challenges and may come up with different answers, transformational business practices are necessary to compete globally. These practices will drive the innovation and speed required to help companies outpace their competitors.

The good news as you start on this journey is much of the data already resides in your plant. Harnessing the information and using it to transform the business is the key. Focused outcomes and approaches that support scalability enables measured investment and supportable business cases.

The path to digital transformation is not an easy one, but success can be realized by taking one step at a time, starting with the most pressing problems (see Figure 6).

Most manufacturing plants and facilities have implemented automation programs, and these have produced a wealth of data available for driving digital transformation. This has created opportunities to use data to first address immediate and pressing needs. Moving forward with IIoT implementations in this manner allows digital transformation efforts to start small and scale up, greatly increasing the odds for success.

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