HMIs Open the OEM Machinery Aftermarket

HMIs Open the OEM Machinery Aftermarket
HMIs Open the OEM Machinery Aftermarket
Machinery original equipment manufacturers (OEMs) produce capital equipment, most of which remains in service for decades. This long lifespan means new equipment purchases can be few and far between, so OEMs have always looked for ways to support their customers while cultivating an ongoing service and support business. New technology is making it possible for these OEMs to re-engineer their processes and operations, better support their customers, and capture increasing aftermarket business.
Aftermarket business can involve more than just the classic replacement parts and repairs. New options with digital services make remote maintenance and upgrades possible. Extended aftermarket services provide a stable revenue stream and good margins for machinery manufacturers, while often lowering costs for their customers as compared to having them perform this support in-house. These services also enable OEMs to better understand their customers’ operations by gathering valuable data about their equipment and operations, which can be used to identify issues and improve future machine designs.
Human-machine interfaces (HMIs) are a key industrial technology positioned to help OEMs take the next step to delivering advanced aftermarket support. This article describes how OEMs can incorporate modern HMIs to offer these services to their end user customers.

Expanding Role of the HMI

Basic machine HMIs are software running on a PC or other hardware, and these are typically tasked to only provide visualization of operating information for plant personnel. The rapid progress of computing hardware, software, and networking available on the factory floor means much more is possible.
Some HMI software systems have evolved to incorporate new features, such as allowing processing and analytics to happen right at the HMI, as opposed to being processed at some more complex higher-level system (Figure 1). Sensors and other connected devices right at the machine are used to not only handle basic equipment functionality, but to also derive useful machine metrics.

Figure 1: Traditional machine HMIs provide only operational visualization, but the newest products like ADISRA SmartView support advanced analytics right on the factory floor.
The simplest metrics are performance parameters like operating speed, parts per minute, uptime/downtime, and the like. When aggregated and evaluated in context with each other, basic metrics can provide much more comprehensive information, such as overall equipment effectiveness (OEE), and can also be used to predict machine failure. When end users have this information in hand, they are able to optimize their operations.

Getting the Info Out

Standard HMI software displays machine information and alarms locally. This situation has improved incrementally over the years with networking and other capabilities, but there has been a tendency for HMI vendors to add features in an attempt to accommodate any conceivable machine, process, or end user need. This is sometimes welcome but can introduce excess cost and complexity.
Modern HMIs still need to provide visualization, but not only on-board the machine. They should be capable of operating on touchscreens, tablets, mobile devices, or any web browser (Figure 2). For best overall performance with machine automation, an HMI also needs the ability to create and display machine metrics. Furthermore, modern machine HMIs should have native features for providing real-time analytics and pushing this information to the cloud for enterprise access and historical recording.

Figure 2: Machinery OEMs and end users are looking for operational and analytical visualization to be delivered anywhere, on mobile and desktop devices.
It is important for these modern HMIs to be designed and built from the ground up with a small footprint, able to be installed and run reliably on increasingly capable edge devices of all types. For the most extensible viewing options, displays should be rendered using HTML5. ADISRA SmartView was specifically created with these considerations in mind, making it ideal for embedding into machine, field, and OEM devices at the edge of the network or local on the machine.
These features transform the traditional HMI into a smart device that can report status and what has been happening over time with a machine. The ability to collect, present, and report analytics is now a requirement for machine builders addressing aftermarket services and solutions for their customers.

Leveraging Machine Data

Machine builders have a deep understanding of design, constraints, and best operating practices for their equipment. They are ideally positioned as the optimal source of key performance indicator (KPI) data for their machines. Applying their knowledge base is a natural extension for OEMs offering real-time support and maintenance services via the cloud for their machines.
With the right HMI software running on edge devices, secure remote connectivity and historical data collection with real-time analytics makes machine builder aftermarket service a reality. This real-time monitoring of equipment helps end users create value by optimizing operations, and also provides support and proactive parts delivery so the end user avoids any unplanned downtime and the collateral costs associated with it.
Modern HMI software can be built into new machines but is also a good way for machine builders to connect their legacy hardware to the cloud for aftermarket service. This allows machine builders to extend the serviceability and performance of legacy machines, also a valuable benefit for the end user. Existing equipment can be improved by adding OEE and KPI information, resulting in reduced use of energy and consumables, along with reduced downtime and increased throughput (Figure 3).

Figure 3: Modern HMI software such as ADISRA SmartView helps OEMs and end users alike by enabling performance monitoring, optimization, and improved support options on new and legacy equipment.
With the ability to send this information to the cloud, machine builders can build an expanded knowledge basis of information across all their customers. This availability of deep historical data, sometimes called big data, is necessary to take the next steps toward machine learning for identifying anomalies, which can help predict equipment failures before they happen. This type of predictive maintenance permits ordering necessary parts in advance and performing maintenance only as needed. Eliminating nonessential maintenance reduces costs, delays, and unplanned shutdowns.
Another advantage of collecting machine performance data spanning a large customer base is a better understanding of how customers use their machines, and in turn incorporating that information to refine machine designs. This capability fully closes the loop on the design cycle, ensuring that machines are built in the best way to satisfy customer needs.
Some HMIs have been used in the past as basic data collectors, transmitting data from field or control devices, and sending it to a knowledge base in the cloud. The next evolution is using HMIs to push computing and communication power closer out to the field and onto the machine. The more universal availability and interconnected nature of this data enables machine builders to more readily turn information into action.


Another possibility when using evolved HMIs to supply real-time big data is a new business model for owning, operating, and maintaining production machinery. Traditionally, end users have bought or leased machines. Now it is possible for end users to reduce their capital investment by operating machines on a machine-as-as-service (MaaS) model.
Two types of MaaS models are popular today. One is where machine builders sell the machine at a discounted price and receive a small sum for every item produced by the machine. Another is a subscription-based model where machine builders supply the machine to the user at no charge—and then monitor, maintain, and repair the machine on an ongoing basis for a subscription fee based on some combination of in-service time, machine availability, and production.
End users may use many types of machines, some of them not related to their core product business. For instance, an end user may produce devices or goods in an area where they have extensive expertise, and they may need packaging machines to box the products for sale but have less experience in this area. By shifting some of their non-core operations—or even all of their production—to MaaS, end users are also shifting some of the risk and liability to machine manufacturers. The end user can then focus on their core business as they effectively outsource some of their other needs.

Machinery Builders and End Users Benefit from Modern HMIs

For typical industrial equipment and machinery, the purchase price is only a small portion of the overall cost because significant costs are incurred in the form of ongoing operating expenses. Machine builders can use new technologies to develop creative ways for helping their customers get maximum utility from their machines by preventing downtime and optimizing operations.
In many ways, machinery HMIs are a mature technology. However, today’s edge hardware combined with clean-slate HMI designs aimed at machine builders are making possible new ways to design, supply, own, operate, and support these machines.
A versatile HMI software suite, like ADISRA, empowers machine builders to provide their customers with remote diagnostics, maintenance services, machine OEE, predictive maintenance, and MaaS options. These services help OEM customers be more productive through maximized asset availability.

About The Author

Marcia Gadbois is the president and general manager of ADISRA. Marcia is an entrepreneur who has grown a start-up from inception to a successful liquidity event. Prior to joining ADISRA, Marcia was the President of InduSoft, which was acquired by Invensys. In the past, Marcia held a number of high-tech senior management positions in the area of business development, strategy, competitive intelligence, marketing, and sales. Marcia has more than 34 years’ experience in the software industry in diverse technology areas such as artificial intelligence, operating systems, rapid application development environment, output management, databases, directory services, data recovery, middleware, and industrial automation. Marcia is a contributing author in the book, “Client/Server Programming with RPC and DCE” as well as author of many articles and whitepapers. Marcia holds a BS in Management Information System and Computer Science from Bowling Green State University and an Executive MBA from University of New Hampshire.

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