Digital Transformation of Manufacturing Industries

By Greg Gorbach

Category:
Industry Trends

The next several years will bring about the “digital Transformation” of manufacturing industries.  This will touch nearly every aspect of business as existing systems, jobs, and business processes are instrumented, redefined, and optimized with artificial intelligence.  This transformation will be widespread and far reaching.  Information technology (IT), operational technology (OT), engineering technology (ET), supply chain, asset management, services, and customer-facing systems will all be impacted. Discrete manufacturing, process industries, utilities, energy, infrastructure, and more are already beginning the transformation. 

Digital Transformation of Manufacturing Industries Trends

It is real, but it’s difficult to say how long it will take.  It will surely take many years to fully realize, but is already happening faster than many expected.  This blog presents some of key trends ARC tracks today.

Advanced Analytics and Machine Learning

The most noticeable and probably most important trend today is the proliferation of advanced analytics and machine learning (artificial intelligence, cognitive computing, etc.)  The technology has reached a tipping point and can now deliver value in setting after setting.  In turn, this fuels demand for smart connected sensors, digital networks, and other ways to collect and move data to the analytics systems – and vice versa.  Is mass displacement of workers on the horizon?  Perhaps.  But it is clear that these technologies will result in substantial change.

Platform vs. Platform

Cloud application platforms provide a modern approach for developing and deploying software applications. The approach is gradually displacing the older client/server model, in which large, complex, monolithic applications were created and run. In industrial companies, the client/server model came to dominate both the IT and the OT software spaces in recent decades. The pace of this changeover is accelerating, however, as more and more companies embrace the modern platform approach. This has also sparked a “platform vs. platform” competition in the marketplace, with large suppliers seeking to establish the dominant platform ecosystem and the broadest library of third-party applications and smaller suppliers trying to figure out just how they should compete in the emerging environment.

Open Systems

We can see the drive toward open systems in two levels: the platforms/apps level and the automation level.  At the platform/apps level, many of the competing cloud platforms are based on the open source Cloud Foundry platform.  At the automation level, ExxonMobil and The Open Group are the primary movers behind an open process automation initiative, although Namur has a complementary effort in progress.

Supply Chain Digitization

As the digitization of the supply chain progresses, new approaches are disrupting established business models.  Omnichannel retailing uses a variety of channels in a customer’s shopping experience, including research before a purchase.  These channels include retail stores, online stores, mobile stores, mobile app stores, and telephone sales.  The customer dictates how a transaction occurs. Digitized systems and processes facilitate the customer journey to transact and be served.  Digitization also enables personalization of products and services, and customers increasingly seek out personalized products or prefer to shop where they can select from larger assortments of SKUs.  Autonomous vehicles and enhanced product, pallet, and container tracking and real-time status are also making inroads in warehouses and on the highways. 

Edge and Fog

Cloud-only approaches can no longer keep up with the volume, latency, mobility, reliability, security, privacy and network bandwidth challenges of the industrial plant. Fog computing distributes compute, communication, control, and storage closer to where the data originates, enabling faster processing time and lowering network costs.  Fog pools the resources and data sources between devices that reside at the edge and other nodes in the network. Any device with computing, storage, and network connectivity – such as industrial controllers, switches, routers, embedded servers, and video surveillance cameras - can be a fog node.

Smart Products and Services

By offering smart, connected products, manufacturers can position themselves to improve their customers’ experience with their products.  Digitization enables manufacturers to improve the performance of their service operations through remote connectivity and enables predictive maintenance; continuous uptime; rapid service response; and the opportunity to offer incremental, revenue-producing products and services.

Product-as-a-Service

Another trend is the migration from selling products to selling the value of the product, or product-as-a-service.  Examples include an aircraft engine builder billing airlines on the amount of thrust provided, instead of just an aircraft engine and a maintenance contract.  A compressor company sells compressed air as a service, instead of compressors. 

By selling outcomes or product-as-a-service, a manufacturer or OEM retains ownership of the asset itself, and provides all required maintenance, service, and repair to meet agreed-upon service level agreement (SLA) levels. 

Smart Factories, Plants, Operations

In plant operations, digitization means we must recognize that digitization involves connectivity to much more than the production machines and systems.  Wearables, augmented reality helmets or glasses, mobile devices, smart carriers, smart containers, smart components, smart products, autonomous machines, video, third-party services, social applications, additive manufacturing, voice control, remote sensing, and more are now an active part of the real-time, data-rich environment in the plant.  Autonomous inventory movers can navigate independently throughout the manufacturing plant, delivering components where needed and on time.  Still, connectivity only improves performance when advanced analytics and execution software are also applied. 

Additive Manufacturing

Additive manufacturing continues to make unbelievable strides towards the manufacturing mainstream.  It has progressed farther and faster than almost anyone foresaw. Driven by materials science and design software advances, this technology can already build optimum parts – in significant volume – that cannot be made any other way. The hype around 3D printing may have died down, but it may be the most potentially disruptive technology in manufacturing.  Companies that neither prepared for or anticipating its emergence on an industrial scale could soon find themselves at a significant disadvantage.

Asset Performance Management

Improving asset performance can improve efficiencies in two main areas: enhancing production performance and offering new business models and services based on smart, connected products.  That being the case, it’s no surprise to find many solutions focused on predictive maintenance, asset analytics, and asset management.  There are opportunities to better utilize assets, coordinate with operating and business needs, improve the availability of replacement parts, and improve the efficiency of field service groups.  Equipment manufacturers are rapidly adopting IIoT to offer asset health monitoring and predictive maintenance subscriptions to create new sources of aftermarket revenue.

Smart Environments

A smart city is connected, intelligent and optimized by a municipality to reduce costs, increase safety, attract investment, be sustainable, and enhance livability.  Smart cities depend upon the digital enhancement of assets and the deployment of sensor networks with ubiquitous multimodal connectivity and smart governance.  Smart cities present tremendous opportunities for industrial IoT, but challenges abound.  Technology innovation often outpaces policy, including standards for data privacy.  The bureaucratic red tape involved with government contracts also remains a major obstacle.  Startups with novel solutions are shut out of the contract process and the transition to service-based models does not align with the often-archaic government thinking and processes.  Nevertheless, the trend towards smart cities is clear. 

Digital Transformation of Manufacturing Industries Top Hurdles to Overcome

Despite a great deal of industry activity, some real progress, and growing comfort with the cloud; issues related to cybersecurity, data security & privacy, and confidentiality still lead the list of hurdles to be overcome.  Approximately 55 percent of the respondents cited this as a hurdle (19 percent Leaders and 36 percent Challengers).  Put another way, 45 percent of respondents did not cite this as a hurdle – which suggests that while this is an important concern, it is not necessarily a showstopper.  With all the digitization activity currently under way, this shouldn’t be surprising.   

Another group of leading hurdles or obstacles relate to technology issues arising from the fact that today’s plants aren’t highly connected yet.  It’s a big part of the digitization work to be done.  These include:Digital Transformation Top Hurdles

  • Lack of strategy for dealing with legacy systems and equipment
  • Limited availability of machine health data
  • Complexity of potential solution space: where to focus?

The other leading hurdles are not about technology; they are normal business issues:

  • Lack of budget (39 percent; 8.6 percent Leaders)
  • Management vision and buy-in (39 percent; 7.6 percent Leaders)
  • ROI or business case for digital transformation (38 percent; 10.4 percent Leaders)

It’s worth taking the time to examine the rest of the hurdles in the chart, not because any one stands out as a showstopper, but because this list is a pretty good proxy for the kinds of issues that might arise in any digitization journey, and it is a good idea to think them through in advance.  

Digital Transformation of Manufacturing Industries Opportunities

Business Transformation

The move to digitization has been sold, at least in part, based on the possibility of significantly improving or transforming the business.  About half of the respondents see opportunities for new business models and revenue streams, as well as opportunities for improving business responsiveness and agility.  ARC frequently sees this expressed as “moving closer to the customer.” It is sometimes realized through new service offerings based on connected products or other customer needs.  For example, in the paints and coatings market, companies have begun offering online design services to help customers select and visualize color schemes in advance.  An element of creativity and innovation is needed to bring about a business transformation.  Even though they may not quite see the shape of the change, about 40 percent of respondents see opportunities to grow existing markets, increase market share, or create new markets. 

Digital Transformation of Manufacturing Industries Opportunities

Performance Improvement

It is useful to examine the expected performance improvement opportunities from the perspective of the respondent.  Here we look at the top performance improvement opportunities identified by those whose focus is either Business, Supply Chain, Operations, and Engineering and Maintenance.   

From a Business perspective, plant operating performance tops the list, but sustainability and compliance, demand forecasting, and warehouse operating performance are also important.  The Supply Chain group sticks to its “knitting,” identifying related opportunities as top opportunities in this order: demand forecasting, inventory optimization, warehouse operating performance, sustainability and compliance, and transportation operating performance

Digital Transformation of Manufacturing Industries Opportunities Performance Improvement

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