The future of production across industrial sectors will lead to an augmented adoption of robots, AI and IIoT, which will positively impact the motors and drives market, as Susan Fearn Ringsell discovers.
Almost all industries are spurring changes since motors and drives are now implemented across many more applications. Meanwhile, applications are requiring additional intelligence to deliver critical information to the operator and the enterprise.
“The increased focus on the use of robots for industrial automation is one of the significant factors driving this market’s growth,” says Julijana Ristov, UK business manager – large drives products, Siemens UK & Ireland.
“This requires a balancing act between innovation and continuity,” explains Ristov. “On the one hand you have to design production more flexibly to launch products faster and satisfy individual customer requirements. On the other hand, companies must comply with regulations and ensure process safety and high product quality standards are met.”
According to Bruno Adam, Omron’s mobile projects director Europe, there are several factors involved in adopting automation systems: “The first important factors are quality and design, and in combination with these, the purchase decision is also affected by the price.
“The second is the conception of the complete equipment, which is always also based on the module idea.
“The third key factor is flexibility, which can help to make the right decision for the customer.”
The increased focus on the use of robots for industrial automation is one of the significant factors driving this market’s growth
Julijana Ristov, UK business manager – large drives products, Siemens
Over the last 10 years, innovations in connectivity, intelligence, safety and control capabilities have led to many Variable Frequency Drive (VFD) advancements.
“This has included a growing need for common, motion control technologies across both the motion and VFD portfolios, as machines were increasingly using both platforms,” explains Evan Kaiser, portfolio manager for low voltage drives, Rockwell Automation.
“Whether it’s the conveyor at a food and beverage plant or a servo press at an automotive factory, customers are using drives to precisely control the machine while simultaneously providing diagnostics and machine health information through networked connections to the controller.
“With ADC [automatic device configuration], the recovery of the IP address, drive firmware and drive configuration can all happen automatically,” says Kaiser.
Getting personal
Adam adds: “Another interesting trend is the personalisation and customisation of products.
“Outside the FMCG space, manufacturers know that if they could offer the customer more choices, it would result in higher sales – to accomplish that, they need to rethink the way that they operate.”
The current manufacturing philosophy is based around a linear production line. This works well when you have demand for a high volume of identical goods.
“However, if you want to deliver the same volume of goods, but offer a wider variety of choices, the production line isn’t the most efficient way to accomplish that,” says Adam.
Some forward-looking manufacturers are moving to a cell-based approach to increase the variety of what they are offering, but that also brings challenges.
Conveyors are ideal for a standard production line, but don’t work well in a non-linear environment.
Both servitisation and digitalisation requirements are also impacting growth in the market. Applying a digital manufacturing process doesn’t just benefit product development, it can also optimise factory design and layout.
Ristov says: “We are increasingly hearing the term Digital Twin [Digital Twin uses data from sensors installed on physical objects to represent a near real-time status].
“If, for example, we have to design a pump with a motors drive, with today’s virtual reality capability we can design a product, test it and experience a near real-life status.
“Siemens’ motor products will have both static data and dynamic data available to be used.”
Within a few seconds, operators will be able to gain full access to static product data: manuals, documentation, and spare parts. In parallel, users will be able to stream dynamic data from the product to the industrial cloud through smart boxes and devices.
According to Paul Pryor marketing manager for drives at Schneider Electric. “Data is now critical to ensuring that process plants, lines and machines are performing to the expected levels.
“Smart devices that not only control the process, but log and supply process critical data, are opening up the process industry to levels of decision-making options that have been hard to achieve with conventional products.”
The digital world delivers more comprehensible and actionable data than we have ever had before. By replacing gut feeling with intelligent, real-time data, companies are in a far stronger position to be able to make better decisions.
Another interesting trend is the personalisation and customisation of products
Bruno Adam, projects director Europe, Omron
“Companies that can support and easily adopt servitisation business models [creating value by adding services that are able to work with their customers and truly understand their requirements] will enjoy increased market share,” says Riskov.
Increasingly, sensors and equipment that contain smart diagnostic features are being used across industry to generate large volumes of data.
Riskov continues: “We then need to think about how we make data accessible, secure this data in an industrial secure cloud, and get the right data to the right person in the required format at the right time, so the correct decision can be made.”
Doug Weber, business manager, remote monitoring services – Rockwell Automation, comments: “According to Technavio analysts, the market for cloud-enabling technologies will grow nearly 15% annually through 2020.”
Through cloud-based, asset-performance management capability, companies – such as Rockwell Automation – provide machine builders with a secure way to move data from a machine to the cloud, and then to easily visualise and analyse that data in whatever way it makes sense to them and their business.
Weber says: “In many cases, machine builders may initially be looking for some insight into how a machine is performing in the production environment – measures such as OEE [Overall Equipment Effectiveness], downtime, cycle time and running time are important.”
Design approval
Having that information, especially across a whole fleet of machines, could enable the machine builder to improve the design in the future and drive higher performance.
Weber continues: “Once machine builders start getting data about machine performance, they may look to expand the application to include consumables monitoring, enabling of service contracts, and predictive analytics.”
Machine builders will differ in how they expand their monitoring capabilities based on their business model, differentiators and plans to use application data to further increase their business.
In addition, machine builders are considering providing more extensive diagnostics, or even predictive analytics, around the machine’s performance. This data can then be analysed to predict and prevent future downtime events.
“This is about transforming digital data into digital intelligence by using the thousands of touch and sensing points across a plant and advanced analytics to help customers recognise patterns and make informed decisions based on patterns instead of individual measurements,” concludes Riskov.
