According to AI-powered machine health management company; Senseye’s “True Cost of Downtime” report, unplanned downtime in the period 2021-2022, cost the Fortune Global 500 companies almost $1,5tn. Up from $864bn two years ago. [Source]

Downtime’ is a dreaded term in manufacturing, and while downtime is part of life in a factory, most manufacturers strive for managed or “planned” downtime, where the expected and predictable time required for changeovers, setups, routine machine maintenance, etc. can be figured into capacity and production plans. While planned downtime is manageable, unplanned downtime is unpredictable, expensive and should ideally be prevented and avoided altogether.

Predictive maintenance using condition monitoring

Predictive maintenance monitors the performance and condition of equipment during normal operation to reduce the likelihood of failures. Condition monitoring (CM), or condition-based monitoring, is the process of monitoring specific parameters in machinery such as vibration or temperature to identify changes that could indicate a developing fault. Condition-based maintenance uses data collected during monitoring to perform maintenance at the exact moment it is needed, before a critical failure occurs. CM is a crucial part of predictive maintenance and is useful for maximizing productivity, increasing useful life and value by reporting faults early, recommending maintenance and repair and ultimately optimising production levels.

Condition monitoring is not new and most operators will readily acknowledge the need for CM techniques. Popular CM techniques for monitoring rotating machines usually involve vibration, electrical, thermography and oil analysis. But these methods fall short due to expensive setup costs, space constraints, sensor reliability concerns and limited predictive capacity, all issues that have ultimately resulted in a low or slow adoption of this technology, until now.

 

Introducing Mainitor’s IoT-based condition monitoring solution

Mainitor joined the Savant portfolio of companies when they participated in the Savant Sibanye-Stillwater BUILD programme in 2022. Using an IoT-based condition monitor (CM), Mainitor’s system collects, localises, processes and classifies acoustic data in order to predict machine faults, reduce downtime and increase the lifetime and productivity of large, expensive machines all by using acoustic sensing.

Mainitor CEO and co-founder Chumi Ogbonna explains; “It’s not that CM solutions did not previously exist. Rather, it is more that historic CM solutions were expensive to implement and couldn’t guarantee results. We wanted to fix that.”

Acoustic-based condition monitoring detects and monitors sonic and ultrasonic waves released by moving machinery and materials under stress. Unlike traditional methods, acoustic sensors can be implemented quickly, cheaply and without physical contact with the machine. The collected acoustic signals can then provide relevant information about the machine’s health.

“Mainitor’s combination of acoustic and IoT-based condition monitoring is set to transform the industry. Using a cost-effective, user-friendly acoustic and machine learning solution, Mainitor is able to deliver advanced condition monitoring services that are accessible to large and small clients alike.”

“Mainitor’s combination of acoustic and IoT-based condition monitoring is set to transform the field. Using a cost-effective, user-friendly acoustic and machine learning solution, Mainitor is able to deliver advanced condition monitoring services that are accessible to large and small clients alike,” Chumi explains. “By enabling connected communication between machines, real-time data analysis of an entire production process becomes possible, enabling operators to quickly and efficiently identify and address problems, regardless of the scale and complexity of the tasks performed.”

 

The benefits and implications of the Mainitor system are significant

Connecting and monitoring machines in this way offers comparable data analysis of an entire production process not just individual machines, regardless of whether those machines are carrying out similar tasks or not. As soon as a change in running levels is detected across the chain of production, operators can assess where the problems may be and act upon imminent faults.

The benefits of Mainitor’s IoT-based acoustic CM include:

  • early fault detection and prediction;
  • fast and simple model development when used with Artificial Intelligence;
  • global monitoring feasibility;
  • cost-effectiveness compared to other sensors,
  • protection of other assets;
  • elimination of unnecessary routine maintenance; and
  • faster, more affordable repairs.

 

Assisting Mainitor to grow and expand

Mainitor’s vision is the perfect fit for the Savant/Sibanye-Stillwater iXS Build Programme. As a deep tech, hardware technology investor, focusing on science and engineering innovations, Savant is uniquely positioned to assist companies like Mainitor with their growth and development. As Chumi notes, “Savant has been instrumental in helping us design our solution, while also assisting us in access to future customers.”

As part of the BUILD programme, Mainitor has enjoyed the dedicated support of the Savant team. Savant’s CEO Nick Allen commented: “Mainitor’s solution has industry-shifting potential. Their ability to provide real-time insights and solutions, while bringing transparency and ultimately eliminate operational shutdowns and downtime is a game-changer. The combination of IoT and condition monitoring is the future, propelling the industry forward. We are excited to be working with them and look forward to seeing the company grow and expand.”

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