- By Bill Lydon
- November 11, 2022
From workforce changes and supply chain disruptions to evolution of semantic data models, socioeconomic trends push industry to respond. This feature originally appeared in Bill Lydon's 7th Annual Industrial Automation & Control Trends Report.
Economists, futurists and others in the business of predicting change and helping others adapt often point to societal and socioeconomic forces as drivers of both disruption and opportunity. These macroeconomic drivers transcend time and technology to create new opportunities for manufacturers as well. Here, we’ll explore some of the megatrends that are playing out on the world’s stage and how they are industrial businesses.
The labor shortage means two things for manufacturers: Low labor cost is no longer viable as a competitive advantage, and, therefore, automation is a necessity to be competitive. The good news is that this results in increased productivity, quality and efficiency. However, automation requires an upskilled, educated workforce to facilitate it. Now more than ever, manufacturers must face a changing environment in which these workers demand higher wages in return for the greater value they are delivering.
It pays to keep in mind that wages and employee training are good investments. Enterprises that continually allow their employees to learn about new technologies, methods and techniques are at an advantage, because they are less likely to be surprised, and their businesses less likely to be disrupted by a competitor’s manufacturing and automation innovations.
Also, relying on current vendors for manufacturing technology or hoping that a salesperson knocks on the door with a miracle product that improves business dramatically limits the possibility of success, and may in fact set a company on a path to failure. Instead, the mega trend we are seeing in reaction to the labor shortage is paying more to get more.
Similarly, productivity and responsiveness are being improved with technologies that directly connect workers to manufacturing systems and make them an informed, integral part of production in real time.
Examples are mobile computing and communications technology. The connection of workers is being accelerated by the wide, expanding range of commercial off-the-shelf technologies including voice and video headsets, smart glasses, and virtual reality devices. Further, the various available systems are providing workers with such productivity enhancers as:
- Manuals anywhere
- Equipment identification and lookup
- Real-time superimposed data
- Audiovisual linking to subject matter experts
- Direct access to inventory availability.
Tools such as these can also reduce overall manufacturing costs.
From the customer’s perspective, this trend meets their growing requirements for relatively quick product customization and the ability to see the status of their orders, including the production history. Thus, digital technologies are enabling new connections between manufacturers, their end users and all parties in between.
As a result, many manufacturers are rethinking how they interact with customers and developing business models and revenue streams made possible by digitalization.
Real-time dynamic supply chains
Synchronizing supply chains with manufacturing requirements optimizes production efficiency. Supply chain visibility has never been more critical since the pandemic in coordinating production and shipments.
Environment preservation and sustainability. Manufacturers are recognizing the need for energy efficiency, climate protection, and sustainability. A major part of achieving these goals is digitalization. Advanced controls and automation, accelerated by machine learning, artificial intelligence, and other technologies are helping make it possible for companies to commit to sustainability programs.
Disruptive innovations adopted by manufacturers are achieving superior results, whether they are new applications in existing processes or ones that totally replace traditional methods. Industrial examples include replacing mechanical methods (i.e., cable, pulley) with hydraulics or gearboxes and mechanical camming with programmable coordinated motion with mechatronics.
The subtle part of disruptive innovation is that many times it is the result of using current off-the-shelf technology creatively in conjunction with new technology. By combining the old and the new in novel ways, better solutions arise that provide significant improvements, ease of use, and additional functions.
Many times, established suppliers see the disruptive innovations as unattractive for a range of reasons and try to ignore them. An example in the industrial automation industry is the initial resistance of traditional suppliers to replace proprietary human-machine interface (HMI) hardware and software with PCs and Windows-based software. A recent example related to industrial automation and manufacturing is a “smart helmet,” a safety helmet combined with goggles that displays instructions, safety information, and mapping on the wearer’s safety screen.
Companies that do not take advantage of the appropriate disruptive innovations are likely to become uncompetitive at some point and to be leapfrogged by their competitors. Conversely, companies that leverage disruptive innovations position themselves to become leaders in their industry.
Technology cost and reliability
Commercial technology, including smartphones, gaming products, tablet computers, automotive electronics, and sensors, have achieved reliability appropriate for industrial automation at a significantly low price point with higher performance. Manufacturing automation requirements for high reliability has meant that commercial technologies were not adopted until they were ready. Now there is a wide range of commercial technologies that meet these requirements. An illustrative example is the Ethernet that was commercially used in the 1970s was adopted in the 2000s for industrial network communications once the technology was proven and incorporated into a single integrated semiconductor chip. Only then was it universally added to industrial controllers.
Semantic information to the edge
Semantic data models are growing significantly, creating relationships between data when the data is organized and providing meaning without human intervention or additional processing. Industrial automation and control is adopting semantic data messaging from sensors and controllers, providing inherently usable information rather than cryptic messaging. Semantic data is structured to add context and meaning that are immediately usable by applications streamlining communications. This improves quality and ensures data consistency. OPC UA and companion specifications are an example of semantic data models that implicitly define how such information relates to realworld applications.
Efficiency is achieved by eliminating the need to decode generic messaging and relate it to applications. Basic examples are a representation of pressure sensors by Modbus registers or an industrial protocol analog representation that must be related to an application by an engineer programming and configuring to define the relationship.
Technologies such as machine learning and artificial intelligence, which are consumers of data, benefit from semantic methods that improve performance, intelligence, and overall services and products. Semantic data makes data relationships easy to understand and simplifies application program development while providing better visualization and efficient data reporting.
Evolving manufacturing industry environments
Major manufacturing and process automation technology leaps come in cycles and have included programmable logic controllers (PLCs), distributed control systems (DCS), industrial Ethernet networks, plant historians, and open user interfaces. Each major industrial control and automation leap has been the application of technology developed and widely used in other applications. For example, even though there was resistance to change, the PLC eventually replaced large banks of relays using new technology.
To overcome current resistance to change, it is important to look back at past manufacturing and process automation leaps to see how far industry has come because of them. Leveraging disruptive innovations and technological developments, the entire manufacturing business is being digitally integrated to create highly efficient, competitive, profitable, and sustainable organizations that rely on digital integration to synchronize and optimize supply chain, customer requirements, plant floor operations, and outbound logistics.
This feature originally appeared in Bill Lydon's 7th Annual Industrial Automation & Control Trends Report.
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