Condition based monitoring for food manufacturer

2 Minute Read

Untitled (2000 x 1500 px)

The Challenge

A leading British manufacturer of biscuits and snacks faced issues with asset downtime and product quality. Inefficient fixed maintenance schedules, manual data monitoring, and poor resource utilisation lead to the following challenges that were impacting product availability, customer experience, and cost:

  • Equipment failures leading to spoilage and lost sales
  • Undiagnosed faults leading to asset breakdown and increased maintenance costs
  • Inefficient assets increasing energy consumption
  • Manual data recording was time-consuming, prone to human error, resource heavy, and posed safety risks due to height access requirements
  • Product quality and shelf life being impacted by temperature and humidity variations 
  • No insight from data collected leading to fault misdiagnosis and unnecessary spend/action.

The Solution

The business installed Unipart’s condition based monitoring system in its bakery production facility.

 The non-invasive system install comprised:

  • Thermocouples (thermo electrical thermometers used for accurate, rapid response in extreme temperatures)
  • Temperature and humidity sensors
  • Real-time data transmission via 4G to a cloud-based monitoring platform 
  • Powerful Paradigm Insight AI driven predictive analytics software
  • Line-side PC setup with visual alerts for machine operators to proactively manage conditions.

Reduced

Asset downtime and maintenance costs

The Impact

Unipart’s solution had the following impacts:

  • Reduced spoilage and downtime: Proactive alerts prevented equipment failures and maintain optimal temperatures, minimising product loss. 
  • Energy savings: Optimised equipment performance based on real-time data, reducing energy consumption.
  • Improved product quality and shelf life: Consistent temperatures ensure product freshness and extend shelf life. 
  • Enhanced maintenance efficiency: Shift from reactive repairs to predictive maintenance, reducing costs and downtime. 
  • Real-time visibility and control: Remote monitoring and data-driven insights with visibility of asset health across stores and distribution centres. 
  • Data driven problem diagnosis: Quick identification of issues, such as failing seals or refrigerant leaks, using AI data analytics and machine learning trained on big data.
Untitled (2000 x 1500 px)

Contact us now

Get in touch to find out how Unipart’s condition based monitoring solution can optimise your operational performance, reduce your maintenance costs, and extend the life of your critical production assets.

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