November 21, 2023 Brownfield Machine Monitoring Solutions

Does brownfield machine monitoring hold the key to unlocking the digital transformation of the manufacturing sector?

Jim Morrish, Founding Partner
Nikita Singh, Lead Analyst
Joydeep Bhattacharyya, Content Editor

Does brownfield machine monitoring hold the key to unlocking the digital transformation of the manufacturing sector? Technology industry analyst firm Transforma Insights thinks that it can certainly help. In a report titled, ‘Digital Transformation in the Manufacturing Sector’ Transforma Insights noted that manufacturing equipment generally has a long life cycle, of up to 25 years, or even more in some cases. It also found that according to the US Bureau of Economic Analysis, in 2015, the average age of an industrial asset in the United States was about 23 years, i.e., very close to likely end-of-life.

This implies that the problem with such equipment is two-fold. First, they are old and need to be monitored more closely for signs of failure. Second, they may not have the latest capabilities in terms of industrial control and therefore lack the ability to integrate data the with organisation’s processes. One of the solutions to such issues is Brownfield Machine Monitoring solutions, and in this blog, we define what they are and explore in detail the benefits, use cases, types of sensors, and examples of deployments of these solutions.

What is Brownfield Machine Monitoring?

Brownfield machine monitoring refers to the monitoring of existing (legacy) equipment by attaching new sensors in order to gather data about performance and machine health, amongst other things. One of the main problems with ageing machines is that they cannot provide the digital data necessary for data-driven decision-making, and the majority of the time, producers in the manufacturing sector do not want to change current, reliable legacy assets in order to implement new technology-based solutions. By attaching sensors to existing infrastructure, owners can bring existing legacy equipment within the scope of their digitalisation strategy.

What are the major sensors deployed by Brownfield Machine Monitoring System?

Retrofit kits are a generally low-cost option that enables legacy equipment to interwork with IoT sensors, advanced analytics, and secure IoT architectures. Sensors that are used to monitor motors and measure vibration and other conditions are relatively cheap, costing around USD100 per piece. A wide range of sensors and monitors are fitted in old machines to get more information about their functioning. In this section, let us learn in detail about some of them.

Audio sensors

These sensors can provide information about the condition of a machine such as the level of stress that an electric motor is under or the condition of a bearing including, thereby identifying if it is failing, or if a stamping tool is working unusually in some way just based on an audio fingerprint. The concept can be retrofitted to almost any machine.

Vibration sensors

These sound/vibration sensors can detect increased wear and tear and predict failures. They typically establish a baseline set of information that relates to ‘normal’ operations. In case different sounds or vibrations arise, they can identify that something is going wrong. In some cases, they may use AI to identify anomalous behaviour.

Optical sensors

These sensors can be trained on existing status lights, dials, or meters, and they report changes.

Plug-in electricity monitors

Such monitors can be inserted between an industrial machine and a power supply, and they report fluctuating demand that can indicate that a machine (or motors within a machine) is stressed or is not working properly.

Remote valve monitors

These monitors can be used to detect the position of hand-operated valves and they report this information to a central control system. This enhances safety and can result in quicker process recovery after maintenance shutdowns.

Some examples of service providers offering Brownfield Monitoring and what do they offer?

In this section, we mention some of the prime service providers and describe briefly their product offerings.

AWS

Its Monitron is an end-to-end system for retrofitting industrial equipment monitoring. The vibration and temperature sensors are glued to the piece of equipment and report data automatically via the gateway. The sensors have an expected battery life of three years.

Bosch

Bosch offers a smart Sound Engineering platform, Sventa, that records/detects faults, and unusual noise levels using wired or wireless sensors and sensor boards and uses AI to provide quick responses to machine failure through alerts and expert connections.

Siemens

Siemens’ Senseye PdM is a predictive maintenance device and includes retrofitted sensors that communicate with a data bank using OPC Unified Architecture (OPC UA) protocols. This allows manufacturing companies/industries to collect performance data with equal proficiency from both new machines as well as machines that are 50 years old.

What are the key benefits of Brownfield Machine Monitoring?

These solutions can significantly enhance process efficiency, wherein easy integration of IoT platforms and software solutions can enhance capacity without disassembly or the deployment of new machinery. In less complex manufacturing environments, such solutions can be easily implemented, and they reduce various operating expenses (such as electricity). They ensure better visibility with integrated machinery and production facilities and improved analysis of an increased amount of available information. For instance, different industries such as chemical processing and pulp and paper factories, and water and waste-water treatment plants, can significantly reduce valve monitoring costs by retrofitting wireless sensors and IoT technology.

Manufacturing companies that retrofit existing equipment benefit from the small additional cost of retrofitting (which is not the case with greenfield monitoring solutions). The risk of deploying a new brownfield machine monitoring solution can be a relatively low since the entire production/assembly line will continue to operate in the same way.

Also, Brownfield Machine Monitoring can continuously monitor production lines, reduce scrap (since the lifespan of the equipment is extended), and eliminate extra workload related to manual data collection.

Where have Brownfield Machine Monitoring solutions been deployed?

Some of the recent deployments of Brownfield Machine Monitoring solutions are:

Siemens Guadalajara

A manufacturer of low-voltage asynchronous industrial motors, Siemens Guadalajara was dealing with a slow production process, due to non-connected machines that operated in isolation with no shared information or visibility. Hence, it deployed its own MindSphere solutions and created a dashboard to monitor the consumption of energy resources in real-time. The firm improved its efficiency by 20% and maintenance performance by 5%.

Sugar Creek Brewing Company

In another instance, the US-based Sugar Creek Brewing Company was losing around USD30,000 a month from the foam generated in beer due to variations in pressure and temperature. Hence, the firm deployed a Bosch Rexroth IIoT Gateway alongside an existing PLC, to report regular fill levels and temperature in the brewery. With easily accessible information and the ability to adjust setpoints remotely, it saved USD120,000 in 2019 alone.

Final thoughts: a low-risk approach to machine monitoring

To conclude, Brownfield Machine Monitoring offers manufacturers solutions that are both low in cost and risk and can enhance the performance of ageing equipment. Manufacturers may uncover useful data for predictive maintenance, process optimisation, and data-driven decision-making by installing sensors onto old machinery. With improved efficiency, reduced operational expenses, and enhanced visibility, Brownfield Machine Monitoring solutions pave the way for digital transformation in the manufacturing sector.

About the report
The report ‘Digital Transformation in the Manufacturing Sector’ examines digital transformation in the Manufacturing sector as enabled by the key technology groups that are the focus of Transforma Insights’ research. These technology groups include: 3D Printing & Additive Manufacturing, Artificial Intelligence, Autonomous Robotic Systems, Edge Computing, Human Machine Interface, Internet of Things (IoT), and Product Lifecycle Management.

Accordingly, the aim of this document is not to chart the future direction of the manufacturing industry, but to highlight key areas of change enabled by new and emerging technologies. The bulk of the report is concerned with discussion of these key areas of change, including an overview of each area, together with analysis of the business impact, and the complexity, timings and risk associated with each area. We also identify key enabling technologies for each area (from the list above) and provide summary details of illustrative case studies that are available in Transforma Insights Best Practice & Vendor Selection database.

The purpose of the report is two-fold. Firstly, from the perspective of a practitioner in the manufacturing industry, the document highlights new and emerging aspects of change that can be expected to impact the industry in the next few years. Secondly, from the perspective of potential vendors to the manufacturing industry, it highlights key emerging areas of opportunity to sell new products, services, and solutions to the manufacturing industry. Our analysis of the key technologies that enable each of the identified areas of digital transformation will help vendors of horizontal (technology-specific) capabilities to identify the contexts in which they may be able to secure new business from the Manufacturing sector.

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