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MES technology will need scale, analytics boost for IoT

Modern manufacturing execution systems already have solid reporting and connectivity, but lack the capacity and analytics to be control centers of the Industrial Internet of Things.

The growth of the Industrial Internet of Things offers nearly unlimited potential to expand monitoring and control in the plant. How does this change manufacturing execution systems, and how does MES technology have to change to move into the world of digital manufacturing?

The term IIoT describes the proliferation of smart connected devices that are permeating the world of manufacturing: many types of inexpensive sensors, control and display devices, all with the ability to communicate through the Internet, plant networks or wireless links. Technological advances and increasing volume have brought the cost down dramatically for these kinds of devices, and sales have increased as a result. 

Smart, connected IIoT devices, per se, are nothing new to the MES world. MES has always been highly dependent on smart devices that collect data in the plant and communicate it to the system along with controllers that accept instructions from the MES. What's new is the sheer numbers of them that are being installed -- to a great extent because of the much lower cost -- and the ready availability of a wide variety of physically small and highly capable sensors that can be installed in places where it may have been impractical or unaffordable before.

MES technology is mostly ready for the challenge

The first requirement for an IIoT-ready MES system is to be able to connect to these devices. Connection and data-exchange capabilities on older MES architectures may be limited to programmable logic controller (PLC) and Supervisory Control and Data Acquisition (SCADA) proprietary protocols and may not be open to standard Internet connectivity.

MES technology has evolved from rigid, hard-coded, limited functionality to more flexible, modular designs that can be tailored to fit varying needs and configurations. Since IIoT will bring more of the plant into the network, there will be an increased need for that flexibility and the ability to configure the solution without changing program code.

New applications to exploit this new data will also be needed along with more links to business applications such as ERP and CRM. In addition to being able to handle the sheer volume and variety now available, the MES needs applications to interpret and use the data and generate the reports, control signals and intersystem messaging that turn the raw data into actions and intelligence.

Consider the following scenario. A production machine experiences a problem that affects the quality of the product being made, an issue that can be detected by the attached IIoT sensors. Let's say it is a machine problem that requires the attention of a maintenance technician. The MES detects the problem and immediately sends a message to the third-party service provider -- via email, text message or phone call to the provider's work scheduler -- to dispatch a repair specialist immediately. The MES then stops the machine before it can make any more bad parts and reroutes the current job to an alternate machine and makes the necessary schedule adjustments for pending work on the faulty machine and the alternate machine. The applicable supervisors and the plant manager are immediately notified. The problem is logged for further analysis and applicable business systems are updated with the changes for proper costing, statistics, product (batch) documentation, quality management and more. All of this is immediate and automatic, preventing the production of bad product and ensuring the fastest possible recovery and documentation.

Many MES today have excellent real-time management reporting capabilities including metrics such as overall equipment effectiveness and laboratory information management system reports. But modern, IIoT-ready MES needs strong analytical capabilities -- predictive analytics, flexible user-configurable dashboards, strong data visualization -- to drive real value from the enormous amounts of data being collected.

The majority of today's MES products satisfy the basic criteria outlined above, but most will need to grow in their ability to handle the many more connections and data sources, the massive amount of data, and additional functions and interfaces implied in the simple example presented here. No mention has been made yet about mobile devices: There will certainly be a demand for mobile access to MES technology as smartphones and tablets become more ingrained in the business life of workers, supervisors and managers across the enterprise. As wearables and augmented reality (AR) become more a part of the landscape, MES technology will have to work with those devices as well. And in the case of AR, a whole new generation of applications will be required.

MES technology is already well positioned to embrace IIoT. The impending challenge for MES is to grow in its capability to handle more data, integrate with more of the outside world (inside and outside the enterprise), and keep up with new technologies and capabilities (AR, analytics) as they become more a part of the digital manufacturing world.

Next Steps

Develop a plan for Industrial IoT

Learn about IoT and process manufacturing

Understand trends in supply chain analytics

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