How close are we to realizing the full vision of Industry 4.0?
To understand where we are on Industry 4.0, take a look back to where we came from, which is Industry 3.0, where machinery of all types adopted computerized controls. Digital controls brought tremendous advantages in terms of the control and accuracy of individual machines, but these controls weren’t developed with an eye toward communicating with each other.
The result has been a proliferation of computerized control platforms, including many different types of information and control displays, several types of data transmission protocols, and a range of proprietary data storage schemes.
More recently, equipment builders have been developing “smart” controls that monitor their own functions, communicate performance, status, and alarm data, and thus make real-time performance trending and historical data analysis possible. Today, it is possible to collect and organize data from families of controls, and even from a variety of different controls and different manufacturers using custom integration.
However, realizing the vision of Industry 4.0 – seamless exchange and processing of mountains of data using intelligent machines that can self-adapt and optimize processes autonomously – is very much in the future.
The 4 Steps of Industry 4.0 Evolution
To understand where we are with Industry 4.0, let’s look at its evolution in terms of four major steps:
- Collecting, summarizing and analyzing common equipment and process data:
Collecting, integrating, and presenting common operating data – KPI’s, measures, reports, alerts, threshold levels – to human managers in “dashboard” form to improve management efficiency.
- Standardizing data in equipment controls:
Develop a common platform and protocols for storing and communicating operating and performance data from different types of processing equipment controls.
- Developing rule-driven predictive analytics:
Intensive analysis of a growing body of “big data” identifies underlying patterns and interactions, forming the basis for the rules-driven software needed to drive predictive analytics.
- Enabling machine learning/autonomous operations:
Rules-driven software that enables machines to identify and respond to recognized patterns of equipment and process behavior, and to react to them automatically.
The Vision for Industry 4.0
For Industry 4.0 to take off, the second step of the evolution must take place—data standardization. That means that, across the rubber and plastics industries, manufacturers will need to agree to build standardized data elements and data registers into the control systems that operate primary and auxiliary equipment, by equipment type (i.e., controls in all dryers, TCUs, or extruders). Along with standardized data elements, they’ll also need to standardize data-communications protocols.
As standardization is achieved, and as common data travels in common formats across many equipment types and processes, it becomes possible to easily collect and analyze huge amounts of process and performance data across many equipment types. At that point, Industry 4.0 proposes that we analyze that data for patterns that enable us to predict equipment and process events and outcomes. These recognized patterns of equipment and process behavior are then codified into rules for “predictive analytics.”
It is these rule-based analytics that set the stage for the final step of Industry 4.0: newer, smarter generations of equipment controls that “learn” by applying predictive, analytics-based rules to real-time operational and performance data, then react to recognized patterns to adjust themselves and optimize process behavior and outcomes automatically.
The Reality of Industry 4.0
Where we are today
Right now, Industry 4.0 work is focused on the first two steps of the process. Through platforms like Conair’s SmartServices, it’s become possible to collect, summarize, and analyze equipment and process data from auxiliary equipment, both Conair and other makes.
Obviously, it’s not difficult for any equipment maker, such as Conair, to gather data from its own proprietary controls, but it’s a bit more challenging and much more expensive to do the integration needed to gather, summarize and analyze data from other proprietary controls.
Work on Industry 4.0 data standardization is underway using OPC-UA (Open Platform Communications-Unified Architecture), a proposed interoperability standard for the secure and reliable exchange of data in the industrial automation systems. An OPC-UA working group for Plastics and Rubber Machinery has completed the first two pieces of a protocol for developing worldwide standardized interfaces for plastics and rubber machines based on OPC UA. To date, this working group has defined standards for IMMs, extruders, and TCUs, with standards for other auxiliaries anticipated in time.
Of course, the new OPC UA protocols, even when completed, are proposed standards and equipment builders would have to accept them, then build them into equipment, and then gain broad equipment adoption among customers—all processes that will take considerable time. Before adopting the new equipment, customers would have to see the benefits of transitioning away from – or coexisting with – current and legacy equipment whose controls rely on the familiar MODBUS architecture that has predominated up to the present.
Serving the Present While Building for the Future
As Conair looks ahead, our approach is to build OPC-UA capability into all types of advanced auxiliary equipment controls, yet continue to evolve with current control systems and protocols used in equipment today. Serving both the present and the future was a key consideration in developing the SmartServices® platform. Conair elected to build SmartServices as a cloud-based application so it could accept data in multiple formats from a growing range of auxiliary equipment. In the absence of data standardization, we integrate the data ourselves, but use SmartServices as a common monitoring, analysis, and control platform.
How processors can get involved now
We believe that SmartServices is essential now, because processors—especially small and medium sized—don’t have the capital and IT resources needed to build and integrate their own process and equipment monitoring solutions from scratch, and they shouldn’t have to wait for the full realization of Industry 4.0 to have a plug and play tool to use. Today, SmartServices offers auxiliary equipment monitoring with real-time trending, machine controls, troubleshooting alerts and support, programmable Key Performance Indicators and threshold alarms, and an expanding range of analytics capabilities.
We chose to put SmartServices on a secure, cloud-based platform – Amazon Web Services (AWS) – because it eliminates processor costs and headaches by:
- Being very easy to implement and install, using machine hubs and Ethernet cables
- Operating across computing platforms and devices
- Providing equal features and functionality to all users, and,
- Automatically providing and managing software updates at all times.
Further, SmartServices leverages knowledge and capabilities that are unique to Conair:
- We’ve provided auxiliary equipment to virtually every type of plastics processor.
- We can capture and integrate “big data” from customers who participate voluntarily in the SmartServices program.
- We have the process, operations, and maintenance knowledge and experience to intelligently sort through big data, identify important details and patterns, and then use those to build intelligent, predictive analytics and someday, the logic needed for machines that can learn and act autonomously.
Bringing Industry 4.0 Capabilities to Life
Industry 4.0 is huge and ambitious vision, whose components can only be achieved in increments. As our industry awaits the realization of data standardization and the long-term potential of predictive analytics, machine learning, and autonomous processing, machine builders like Conair are already beginning to bring Industry 4.0 capabilities to life today.