01225 650150 | 0800 772 0795 sales@austinconsultants.com

Condition Monitoring

Gain new insights and optimise equipment performance with greater predictive accuracy.

Condition MonitoringIoT Condition Monitoring

Converging technologies, machine learning and IoT offers endless Industry 4.0 opportunities for manufacturers to innovate and drive operational efficiencies.

The condition monitoring of production critical manufacturing equipment is fundamental to drive performance.

  • Gain new insights and optimise equipment performance.
  • Prevent outages and minimise production losses from unplanned shutdowns.
  • Allocate resource and schedule preventative maintenance more effectively.

We deploy condition monitoring technology utilising non-intrusive load monitoring, edge analytics, and machine learning, to provide accurate power consumption and cutting-edge insight into the performance of industrial equipment.

In a manufacturing context, this technology can be utilised to improve operation, preventative maintenance, repair and overhaul performance with greater predictive accuracy at the production unit, system, component and part-level.

Many manufacturers already develop products that include aspects of condition monitoring by integrating data collected by sensors already in situ and utilised by day to day operation. However, not all equipment offers this facility, particularly an install base of older units.

Our solution can be retrofitted with minimum disruption to any equipment to provide detailed operational insight. The real-time data can be shared to the cloud and monitored via a user-friendly web or native app, or integrated into a designated platform.

We are able to rapidly develop a simulation, or digital twin, of a system to understand the detail of normal operating parameters and identify when a change or fault develops. With years of experience implementing a wide range of sensors and sensor analysis, our team is able to offer data science for any type of data.

Solution Overview

Our structured approach ensures that you achieve the full potential of your condition monitoring application.

Initial Consultancy

  • Requirements capture.
  • Exploratory data appraisal.
  • Data integration requirements.

Solution Design

    • Hardware – standalone NILM unit/sensors or combination.
    • Software – dedicated stand-alone app and/or integration with third-party systems.

System Development

    • Hardware.
    • Software – bespoke functionality & integration requirements.
    • Onsite installation & algorithm training.
    • User/Admin training.

Maintenance

    • Ongoing maintenance and support as required.

Benefits

  • Discover new insights.
  • Optimise equipment performance.
  • Accelerate innovation and new product or service development.
  • Create and refine better simulations and a more accurate digital twin.
  • Simplify data analysis.
  • Detect faults, changes in performance and operating conditions earlier.
  • Prevent outages, reduce downtime and minimise the fiscal impact of production losses.
  • Increase predictive accuracy at the component, part and system level.
  • Increase reliability, availability & maintainability.
  • Allocate resource and schedule preventative maintenance more effectively.
  • Reduce maintenance and energy related costs
  • Improve preventative maintenance, repair and overhaul performance
  • Improve the safety of personnel & assets.
  • Augment and improve value from existing systems with new capability.
  • Significantly reduced capital costs of plant, process and asset expansions including retrofits.

 

Why Austin Consultants

  • Independent expert review of requirements.
  • Effective budget management via outsourced expertise and transparent project management.
  • Our consultants are experts in software integration, with a proven track record of delivering solutions in product development environments.
  • Our condition monitoring units can be retrofitted to existing equipment with minimum disruption.
  • We offer proven expertise in sensor integration, hardware, software and custom engineering.
  • Our ultra-high sample rates offer greater levels of sensitivity and insight.
  • Our services can be outsourced or we are happy to undertake projects as part of a blended team, working alongside your in-house developers to ensure seamless delivery and knowledge transfer.
  • We have a proven pedigree in delivering machine learning and condition monitoring applications.

 

 

From our blog

NI LabVIEW Vision Demo – Robot playing Air Hockey

NI LabVIEW Vision Demo – Robot playing Air Hockey

Video Demo: Description The system uses the NI LabVIEW Vision tools running on the Laptop to perform high speed object and pattern matching at scan rates of up 80fps to follow both the Puck and the Robot Pusher. Using advanced mathematical...

Hidden Markov Model in LabVIEW

Hidden Markov Model in LabVIEW

Consider this scenario: a guy (say John) has three dice. The shapes of the die are different. Die 1 has numbers 1, 2, 3, 4, 5, 6 on it, Die 2 has numbers 1, 2, 3, 4 and Die 3 has numbers 1, 2, 3, 4, 5, 6, 7, 8, as seen in the following...

A quick update for the Flappy Bird project

A quick update for the Flappy Bird project

It seems that my last post was found by @labview and brought a few visits to this page so I thought I would share an update with you all. The project is still undergoing and I was kind of busy this month but I will try finish this ASAP. Here are some updates since the...

Implement Q-Learning algorithm in LabVIEW

Implement Q-Learning algorithm in LabVIEW

So this is the story: Flappy Bird was so popular that my friend suggested that we should develop a LabVIEW kit with a motor to play it. Two days later, we found Sarvagya Vaish managed to score 1000 by applying Q-learning algorithm. A couple of days later,...

Multiclass classification in LabVIEW using SVM and one-vs-all method

Multiclass classification in LabVIEW using SVM and one-vs-all method

Dr Bo Fu is a Certified LabVIEW Developer and joined the Austin Consultants team in December 2013 as a Systems Engineer. Dr Fu joins us from the University of Nottingham where he completed his PhD and did a Postdoc in Electronic Engineering, developing a high-speed...

News & tips

Sign up to our email newsletter to receive regular LabVIEW tips and related updates from the Austin Consultants team.

Get in touch

Talk to us about your project today.