• Seminar audience.
    Seminar audience.

Cold chain sustainability champion, Dr Rob Lamb, will join an exclusive line-up of speakers to unveil the latest advancements in AI-driven, data monitoring technology and its impact on enhancing the performance and sustainability of industrial refrigeration and heat pump systems.

Dr Rob Lamb will discuss data-led performance optimisation and smart monitoring technology at the upcoming Industrial Refrigeration Network (IRN) Conference, which will take place from 6-7 June, 2024, in Rothenburg, Germany.

He will explain how to integrate AI and remote data analysis to enhance the operational efficiency of industrial refrigeration and heat pump systems throughout their lifecycle.

His presentation will highlight real-world applications from successful collaborations between Star Refrigeration and major multinational retail operators.

Dr Lamb is group sales and marketing director at Star Refrigeration, and he will demonstrate the successful results of implementing AI and live-data analysis technology.

“By sharing Star's methodology and findings, we hope to champion the adoption of technology capable of transforming data into actionable insights to improve the sustainability of business reliant on industrial refrigeration and heat pump equipment,” he said.

Hosted by Bitzer's Schaufler Academy, the inaugural IRN Conference aims to become a cornerstone for future developments in the field of sustainable refrigeration solutions.

The event will bring together key cold chain stakeholders from various sectors, including end-users, contractors, installers, consultants, planners, OEMs, and academia to foster thought leadership, share innovative ideas, and strengthen industry collaborations.

As part of the conference agenda, Dr Lamb's presentation entitled 'How AI and Remote Data Analysis Can Help Improve and Maintain Efficiency of Refrigeration Systems Over Their Operational Life' will spotlight how advances in remote monitoring and real-time data analysis, when combined with AI, enable accurate predictions and reductions on energy consumption, operational costs and CO2 emissions.

“By combining modern refrigeration system energy efficient controls and technology with AI, we are transitioning the cooling sector away from the traditional 'rear view mirror' approach into a new era where refrigeration system issues are not only reported but predicted and solved before they even happen,” Lamb said.

"The technology uses intuitive algorithms that continuously analyse, learn and adapt to optimise refrigeration system performance in real-time.

“Its predictive capability allows it to foresee potential threats -even the ones hiding in- and advice on remedial actions to increase efficiency and reduce CO2 emissions"

Showcasing recent projects where sophisticated AI-led data analysis technology has been deployed to decarbonise and reduce energy consumption, Dr Lamb will share details of the methodologies employed, the actionable insights gained, and the energy and CO2 projections that contributed to energy savings and reduced environmental impact.

The presentation will outline the core sequential steps of the technology's implementation lifecycle, from the installation of sensors to deriving insights and implementing cost-avoidance measures.

Dr Lamb will explain how data gathered from cooling and heating equipment via standalone loggers, APIs, and existing control systems is transformed into a cloud-based digital twin - a virtual simulation that benchmarks ideal system performance against actual data, identifying inefficiencies.

Attendees will also gain an understanding of the operational advantages of online dashboards, which provide operators with a detailed view of system performance, inefficiencies, recommended corrective measures, trends, and estimates of financial and CO2 savings if remedial action is undertaken.

The tool delivers a comprehensive overview and enables multi-site data collection, which allows cooling equipment owners to compare data from various facilities and identify specific focus areas for improvement.

Dr. Lamb will conclude by reflecting on the performance outcomes achieved by current users of AI-driven monitoring and performance optimisation technology.

Specifically, he will deep dive into how the technology enabled Tesco to save 4 GWh in energy costs and over 835 tonnes of CO2e in 21 months, with a return on investment of under 3 months.

 Likewise, Asda achieved a reduction of 5 GWh on energy costs and 1,100 tonnes of CO2e over four and a half years across six distributions centres in the UK.