Top 5 in 2016

Feb. 3, 2016 – Just in time for the New Year, Manufacturing AUTOMATION has compiled the top trends and technologies Canadian manufacturers should watch out for in the next 12 months, as predicted by a handful of industry experts.

Unlike last year’s diverse mix of predictions, this year’s experts all noted the Internet of Things (IoT) and the emerging Industrial IoT (IIoT) as top gamechangers, as well as big data and Information Technology (IT) and Operational Technology (OT) convergence. As Naveen Kumar of Frost & Sullivan (first expert listed below) pointed out, 2016 will be an important year as the industrial sector “readies itself for the digital overhaul.”

Naveen Kumar, Frost & Sullivan senior industry analyst, holds five years of consulting experience in the industrial automation space. He helps companies achieve growth, innovation and leadership with his expertise in corporate strategy and competitive intelligence.

1. Internet of industrial sensors
As machine-to-machine (M2M) communications begin to mature, sensors will be widely deployed to monitor remote assets, measure energy consumption, track environmental compliance and improve asset visibility. Integration of several sensor technologies with edge analytics drives the asset performance, reliability, safety and security. As attention increases towards asset performance management, new low-cost wireless sensors are expected to be deployed in existing installed base to collect several data that were earlier considered inaccessible due to technology limitations and budget constraints. With the improvements in instrumentation technology, miniaturization and advanced analytics software, the cost of intelligent sensors is coming down as well as its ease of use. With sensorization of industrial assets, failing parts in an asset can be spotted very early to avoid undesirable downtime consequences. Process critical applications in asset intensive industries will likely uptake the sensorization to remotely monitor and control at a high level of operational efficiency. The market dynamics around interoperable issues caused by multiple connectivity standards (no standardization) have been keenly observed by the industry participants. However, increased adoption of Internet of industrial sensors in large-scale deployments triggers the best practice solutions, widely accepted standards and market consolidation.

2. Industrial big data analytics
With the increased deployment of sensors and connectivity technologies, emergence of industrial big data pipeline will drive analytics applications for asset maintenance. Software driven assets embedded with analytics at various layers will bring in more intelligence to the system as well as through machine learning. As there is a gap in the market between very broad analytics technology platforms and customer expectations, there’s a lot of work required to build analytic algorithms to address highly specific problems, especially in optimization of asset performance and energy efficiency. First, the biggest challenge lies in building a unique platform to aggregate the variety, volume, and velocity of industrial data and cleanse them before ingesting it into analytic engines. Second, the challenge lies in creating standardized pre-built analytic applications that are flexible, scalable and quickly deployable. This is significant as high implementation cost is the major roadblock in this transformative process. Finally, the focus is to create prescriptive insights collaborating diverse scientific, computational, and mathematical disciplines and business rules to predict business outcomes. It is going to be very interesting to witness how industrial customers are going to build business, whether to outsource managing analytic applications or to handle it internally with in-house expertise from centres of excellence.

3. “As a Service” Cloud models
As Cloud computing enabled significant innovations in enterprise and consumer worlds, it’s now time for the industrial community to witness the impact of Cloud services at the operational level, both in discrete and process based industries. This calls for the emergence of partnership ecosystems to offer holistic solutions that address emerging challenges of end customers. This means the need for an Infrastructure-as-a-Service (IaaS) model that enables industrial setups to concentrate on their core areas and outsource IT processes like storing, managing and securing massive industrial digital assets. Follow on with the IaaS in the industrial sector; it’s the Platform-as-a-Service model that opens up significant opportunities and enables intelligent software applications. We must wait to see how combined expertise from IT and OT solution providers will come together to offer a holistic value proposition that makes industrial customers bet on this transformative approach and improvise their operations.

4. Industrial mobile apps and BYOD
The next obvious technology will be the market for industrial grade apps to address the emerging needs of mobile workers. The increased penetration of 4G-LTE infrastructure will tap the attention of industrial customers to demand mobile interfaces to improve anytime, anywhere response and collaboration. Moreover, the relentless consumerization of IT demands a solution to “Bring Your Own Device” (BYOD), where workers can use a handheld for personal and official activities while ensuring both parties are satisfied with security, usability and cost. The industrial automation market is a classic business case for devices that must bridge the gap between gadgets designed for the general consumer and purpose-built tools for the mobile worker.

5. Industrial cybersecurity
All the above technologies are at stake unless there is a robust back up from industrial cybersecurity systems and infrastructure. Industrial cybersecurity will have to move from a reactive operating model to a more proactive response model. Self-aware systems that can adapt and respond to different levels of trust, decoy systems to gather information on an intruder in the network and defence-in-design are some of the foundational ICS cybersecurity solutions that underpin the growth of Internet of Industrial Things (IoIT) market. Higher levels of IT-OT integration will require appropriate skillsets and solutions that cater to cybersecurity incidents pertaining to ICS. While it is difficult to determine value versus ROI for industrial cybersecurity, damages and costs for repairs and revival after an attack continue to increase with APTs (Advanced Persistent Threats). With the increased ICS security offerings in the market and partnerships, we could see more initiatives from governments and industrial regulations to drive compliance guidelines, possibly for energy sector first and then for the rest influenced by the opening up of industrial network boundaries to the outside world.

Jim Pinto is an international speaker, technology futurist, automation consultant and writer.

1. Internet of Things (IoT)
The industrial Internet continues to transform the automation industry. It revolves around increased M2M communication with vast networks of data-gathering sensors, providing mobile, virtual, and instantaneous connection. The real value derives from the gathering data and leveraging it. More and more infrastructure is being put in place to analyze the data in real time. Cisco estimates that 50 billion devices will be IoT-connected by 2020. Intelligent sensors and networks will take measurement and control to the next level, to dramatically improve productivity and efficiencies in production process. Growth will be bottom-up, not top-down.
 
2. Mobile devices in automation
Today’s pervasive smartphone has more power than a super-computer of just a couple decades ago. The use of Wi-Fi-connected tablets, smartphones and mobile devices is generating strong growth in industrial manufacturing. Handheld devices provide mobile access to real-time, actionable information to decrease costs, increase operating efficiency and enhance productivity. More engineering employees are working at different hours outside the factory. Many organizations are encouraging employees to use their personal mobile devices to access enterprise data and systems, a surprising and perhaps inevitable change in attitude.

3. Cloud computing
Cloud-based applications are the key to leveraging data for improved productivity. IoT doesn’t function without Cloud-based applications to interpret and transmit the data coming from sensors, actuators and plant data from many different locations. The Cloud is what enables the apps to go to work anytime, anywhere. The Cloud helps to optimize operations by enabling collaboration among remote mobile workers and suppliers, allowing fast and secure access for data-driven decisions. Significant gains in efficiency, cost and capability can be achieved as more products become intelligent and Cloud-connected.

4. Smaller, cheaper sensors
Many conventional sensors are still too physically large and expensive, and this limits expanded use in IoT. Systems developers and manufacturers are looking for smaller, cheaper sensors — and they are getting smaller and cheaper all the time. As they do, they will increasingly be used in many intelligent devices. Added sensors and connectivity turn “dumb” products into “smart” ones, while products increasingly move into the realm of services. According to James Bailey of Accenture, “The cost of both the sensors and devices is approaching free and the size is approaching invisible. So, literally everything will have IoT technology at some point.”

5. 3D printing in manufacturing
Today, manufacturing is becoming possible without tooling, large assembly lines or multiple supply chains. 3D printing is increasingly being used for competitive advantage relating to versatility, price and speed of delivery. The technology has developed to the point where it is opening up competitive manufacturing to small businesses. Accuracy is improving, the size of printed objects is increasing, and the price keeps reducing, so that 3D printing is expanding rapidly in the industrial manufacturing arena. It is surprising to think about manufacturing without tooling, assembly lines or supply chains. However, that is what is emerging as the future of 3D printing becomes commonplace.

Larry O’Brien, vice president of research at ARC Advisory Group, oversees research into process automation markets, including process automation systems, process safety systems, plant asset management systems, and field networks. He has been a member on several ISA committees and actively promotes technology standards throughout the process automation industry.

1. Industrial IoT-enabled applications for process automation
By connecting previously stranded data from smart sensors, equipment, and other industrial assets with advanced applications and predictive analytics in the Cloud, IIoT is becoming a strategic enabler to improve manufacturing performance. Despite initial concerns, many companies now realize that, when properly implemented, Internet and wireless technologies can provide appropriate security and availability of services across multiple plants and facilities. This helps further meld plant floor and enterprise systems, creating an opportunity to transform manufacturing operations through IIoT strategies. However, until clear standards and well-defined reference models emerge for IoT in process automation and the cybersecurity issue is fully resolved, many end-users are understandably taking a “wait and see” attitude.

2. Modularization of automation solutions and production processes
Many industrial sectors have already embraced modularization concepts. NAMUR NE 148, for example, spells out how the chemical industry can use more modular concepts in automation and production processes to encourage reusable engineering and more flexible production. This includes use of innovative “plug and produce” micro production plants that can be easily relocated or reconfigured to different products as needed. Modularization also includes new forms of automation hardware like characterizable and configurable I/O and the “late binding” concept between automation system hardware and software to help get automation off the critical path for capital projects. With fully adaptable and standard I/O and control hardware, the user can theoretically design and test all of the software aspects of the system before it is deployed into the physical system hardware. Often referred to as “late binding,” this allows the software to be deployed into the hardware infrastructure at the very late stages of the project.

3. Operator effectiveness and situational awareness
Many advancements have been made in HMI graphics over the past several years and you can see that in the new offerings from DCS suppliers. The most prominent example of this is the adoption of the ISA 101 HMI standard, which addresses both operator effectiveness and situational awareness. ISA 101 probably holds the record for the longest standard in development, but we have seen a lot of progress this past year, with its recommendations being implemented in several supplier HMIs.

4. Freeing “stranded” device diagnostics provides path for intelligent device management
Most intelligent field devices currently installed in process plants are “underachievers.” They have a lot of untapped potential, but tapping into that intelligence and turning it into useful information has eluded many industrial organizations. This is not a question of which protocol to use, whether the devices are wired or wireless, or the kind of plant asset management system in place. The real issues are the day-to-day work processes that determine how maintenance and other tasks are completed in the plant. Preventive maintenance is still the order of the day, with maintenance technicians still travelling out to the field to inspect devices for potential issues. Intelligent field devices, however, offer the potential to change the way maintenance is done in process plants in some fundamental ways. In place of often-inefficient preventive maintenance rounds, real-time digital diagnostics from instruments and valves can be used to schedule maintenance. This enables today’s time-strapped maintenance staffs to focus on the devices and assets that actually require attention. In this manner, maintenance personnel can become more actively involved in optimizing the performance of the plant and operators are in a better position to prevent abnormal situations or shutdowns from occurring. The key is to have the right work processes in place for personnel to follow. ISA-108, an emerging standard, will provide end-users with standard templates for intelligent device management (IDM) work processes that they can deploy in their plants and modify to suit their individual needs.

5. New approaches for integrating automation and electrical technologies
Automation and electrification remain largely separate islands of functionality in today’s plants, as are drives and motor control centres. Both process operators and maintenance personnel have limited visibility into what is really happening in their electrical systems and control over how much power their automation assets are consuming. Many suppliers offer applications for improved visibility into the power side of the manufacturing process. As reflected in our Collaborative Process Automation System (CPAS) model, ARC believes that taking a more proactive stance toward integrating the automation systems and electrical systems domains of the manufacturing process can yield significant energy cost savings. IEC 61850, a global communication standard for substation automation, defines the communication between intelligent electrical devices (IEDs) in switchgear and associated systems. This means that all automation functions, as well as the engineering, can be considered. The main point here is that IEC 61850 is the key enabler for integrating automation and electrical systems. By providing a greater level of interoperability between electrical devices from different suppliers, IEC 61850 does for electrical products what process fieldbus does for instrumentation and control valves. It also promises the same level of enhanced diagnostics and plant asset management capabilities offered in process fieldbus devices.

Andrew Hughes is a principal analyst at LNS Research with his primary focus being research and analysis in the Manufacturing Operations Management (MOM) practice. Andrew has 30 years of experience in manufacturing IT, software research, sales and management across a broad spectrum of manufacturing industries.

1. Real IIoT applications
Much has been discussed about IoT in manufacturing and 2015 has seen the advent of viable first generation IIoT platforms that will allow enterprises to increase the value from their manufacturing assets and products. In 2016, we’ll see the first real applications bringing together data from disparate sources to create knowledge that improves manufacturing. As an example, we can imagine an equipment supplier collecting performance data from many customers and applying it in your plant to improve line reliability and to predict maintenance.

2. Big data analytics
Manufacturing analytics is typically very fragmented. Edge analytics close to control level along with new mobile offerings brings new applications to the shop floor. Similarly, partnerships between automation suppliers and cloud computing companies offers big data opportunities beyond the plant. This year, we expect to see the first real big data analytics delivered to manufacturing companies. These will bring together manufacturing data with unstructured data and external information, and deliver new insights through sophisticated predictive and even prescriptive analytics results. The success of analytics in manufacturing will be directly proportional to the openness of engineers’ minds to new knowledge; new smart connected business processes can come from anywhere.

3. Deconstructed MOM
Manufacturing Operations Management (MOM) systems have been around for almost 30 years and have steadily grown into huge monolithic systems that cover most, if not all, of the ISA95 MOM standard. These systems offer little flexibility. In 2016, we expect to see disruption in this sector from smaller applications that are integrated by IIoT platforms and Ethernet/IP to provide some functionality in the Cloud and some in the plant. Production execution and data gathering will remain in the plant while new applications for scheduling, analytics, visualization from anywhere, traceability and so on will become standalone Cloud applications, often offered as a service. Manufacturers will get more choice, less cost and tighter integration between plants.

4. IoT device gateways
Today almost all information gathered from plant sensors is passed up the chain from sensor to controller to HMI or MOM system and thus perhaps to a centralized repository. The IIoT needs to work in a very different way; access to sensor data that is not needed for control must be easily configured when it is required. New IoT gateways will provide low cost Ethernet/IP connections to the IoT platform and easy access to necessary sensor data without affecting control hierarchies. As IoT applications take off in 2016, device gateways will become an essential element of factory infrastructure.

5. IT-OT convergence
If the first four of my predictions come to fruition, then the fifth is guaranteed true! Plant personnel will see a huge increase of IT professionals wandering the factory floor. The convergence of IT and OT has been slow to get started, probably due to a mutual lack of trust, but now it is time. The opportunities for all involved are limitless as the gaps between plant and IT systems are covered over by IIoT platforms, analytics and MOM applets. All plant engineering staff should make it their 2016 New Year’s resolution to become IT savvy!

Can’t remember how accurate our predictions from last year were? Refresh your memory and check out our Top 5 in 2015 cover story. Do you agree or disagree? Please feel free to send comments and questions to editor@automationmag.com. Happy reading!

This article was originally published in the January/February 2016 issue of Manufacturing AUTOMATION.