Customers: Prepare for a Tsunami of Data
On July 31, 2018 Plex Systems, a cloud ERP and MES solution provider for manufacturing, announced it had completed the acquisition of DATTUS, Inc. a leader in Industrial Internet of Things (IIoT) connectivity technologies. This is an important step in executing on its product strategy, which includes connecting to more IIoT data for more actionable insights, along with enhancing manufacturing and business processes.
As a solution provider of enterprise resource planning (ERP), the Plex Manufacturing Cloud provides the operational and transactional system of record of your business. But looking beyond business transactions, Plex’s goal has always been to connect the shop floor to the top floor. But that is often easier said than done.
While sensors, machines and equipment on the shop floor have been collecting vast volumes of operational data for decades now, that data has not always been “connected” or accessible for decision making. Indeed the very fact that this data collection has been happening for decades contributes to the problem. Many of the machines and software put in place decades ago pre-date the Internet and therefore have no ability to connect to a network. Retrofitting equipment or replacing it is expensive and most of these machines were designed to last a lifetime. Expensive custom integration projects are beyond the expertise and budgets of all but the largest manufacturers. So what’s the alternative?
Providing an alternative is what DATTUS is all about. DATTUS solutions connect manufacturing equipment and sensors to the cloud. Think of it as the bridge between you and your machines. The platform is a hardware/software combination, which collects data from PLCs, VFDs, industry protocols like MTConnect, and popular enterprise applications including Salesforce, SAP and (of course) Plex.
In addition to this plug and play connectivity, DATTUS also brings IIoT data management and industrial analytics. The data management and analytics capabilities previously offered by Plex were sufficient for managing the volumes of data within ERP. But as customers are empowered to bring almost any data stream into the Industrial Internet of Things, they now need to be prepared for a tsunami of data.
Giving Manufacturers a “Leg Up”
The IIoT is just one of several inter-related digital technologies we continue to watch, and what we most often see is limited progress being made in terms of leveraging these technologies. Our 2018 Mint Jutras Enterprise Solution study explored plans and investments in selected digital technologies normally associated with Industry 4.0. We find very low rates of adoption (Table 1) and many have no plans to change that. In spite of all the hype around all these technologies we confirmed many are still sitting on the sidelines of the latest manufacturing revolution.
Table 1: Digital Technologies Plans and Investments in Manufacturing
Source: 2018 Mint Jutras Enterprise Solution Study
*Includes those that expect vendors to deliver at no additional cost
Running legacy solutions based on outdated technology forcibly sidelines some. And others are hamstrung by decades-old equipment on their shop floors. Plex Systems’ acquisition of DATTUS can’t help with the first unless those running legacy solutions are willing to trade up to a more modern, technology-enabled solution. But it can help in connecting those disconnected machines.
While all adoption rates are quite low, we do find IoT has the lowest percentage of manufacturers with no plans and no activity and close to the highest percentage of those that have already made some investment (second only to 3D printing). This tells us manufacturers have at least a grasp of its potential. Indeed manufacturers have been collecting vast volumes of data from sensors on the shop floor for decades. And yet that data has gone largely underutilized because manufacturers fail to connect the data back to the enterprise applications, and the business decisions. And this is where DATTUS can open new doors.
Instead of retrofitting equipment or developing custom connections, the DATTUS platform provides “out-of-the-box” direct connectivity for machines using cellular capabilities. It can capture data from non-networked, discrete industrial assets while remaining agnostic to data type, machine protocol, and infrastructure. It is a hardware-agnostic IIoT solution that can reliably collect and manage data and make it available for further analysis and open doors to several other of the technologies listed in Table 1.
The availability of more data increases the need for analytics in order to make sense of it. The data within an ERP solution lends itself to historical reporting and perhaps even ad hoc queries. Both are designed to answer questions you already have. But where do you turn when it is not intuitively obvious which questions you should be asking in order to optimize production or grow your business?
Therein lies one of the primary differences between reporting and analytics. While reporting answers a series of pre-defined questions, the discovery process and the iterative nature of analytics helps you ask the right questions. Reporting helps you identify a problem. The right kind of analytics helps you avoid it. Reporting seldom helps you recognize an opportunity. Analytics help you seize it.
But as volumes of data start to grow exponentially, you eventually reach a point where the human mind is no longer able to assimilate and cope with that volume. This is where machine learning can add a level of intelligence that is simply not possible without technology. Data sets have grown rapidly in recent years, thanks, at least in part, to information-sensing devices such as those to which the DATTUS solutions connect.
And the shop floor provides us with some of the most often cited use cases for artificial intelligence and machine learning. The ability to constantly scan data collected by machinery and equipment on the shop floor, searching for patterns that have previously led to failures, have saved manufacturers countless hours (and costs) associated with preventive maintenance. By predicting failures, you only need to bring production to a halt to perform maintenance when it is really needed.
Similarly, in environments regulated by strict adherence to specifications, by monitoring sensor data continuously, machine learning can alert operators before out-of-spec product is made. While shop floor supervisors are only able to scan, monitor and cope with a limited amount of data, machine learning knows no such limitations. Machine learning can recognize patterns and correlate data points that a human does not recognize as relevant. And as more data is gathered, it keeps on learning. That is what continuous improvement is all about.
DATTUS adds capabilities for analytics on data-in-motion, quickly providing insights in support of decision making on the shop floor. This includes:
- Anomaly detection (quality control)
- Custom event rules
- Real-time production and efficiency reports
- Performance forecasting
- Predictive analytics
- Machine learning
As part of Plex Systems, we also see the potential of applying these industrial analytics capabilities to the business side of the equation within ERP for supply chain planning, financial planning and budgeting, forecasting and more. The possibilities are endless.
Mint Jutras believes these digital technologies are destined to be absorbed into the enterprise in general, and manufacturing in particular, in much the same way as technologies like artificial intelligence (AI) and natural language processing (NLP) have insinuated themselves into our personal lives.
Think about it. As consumers, we didn’t loudly voice our desire for AI or NLP. But that didn’t stop Apple from delivering Siri on an iPhone. Pretty soon Microsoft delivered Cortana on Windows 10; Google delivered Google Now; Amazon delivered Alexa and now Bixby is on your (newer) Samsung Galaxy. We see these digital technologies being absorbed into the manufacturing landscape in much the same way, as long as solution providers like Plex and DATTUS continue to innovate and push them into the mainstream.
While the technologies in Table 1 are typically outside the scope of ERP, in order for them to be truly transformative, they must interoperate and/or integrate with the enterprise applications like ERP in the front and back office. When purchased separately it is often a daunting task to connect back to ERP and in turn, the business itself. But without this connection, factories don’t get any smarter and neither do the leaders making business decisions. And that’s the real goal of digital transformation in manufacturing: a smart factory and smarter business decisions. And therefore this acquisition makes perfect (and practical) sense.