Andrei Kupchin is an industrial energy-efficiency expert and technology executive who introduced device-level energy monitoring to CIS markets, establishing a regional market for a solution category that had not previously existed there.

Across more than 250 client implementations, he has helped industrial and commercial organisations identify hidden energy losses, reduce operating costs, improve equipment performance, and make better-informed energy decisions.

Drawing on this experience, he initiated and developed a methodology for digital industrial energy auditing that is used by energy-audit companies, professional energy auditors, and industrial enterprises as a practical framework for evaluating and improving energy performance.

It enables audit and plant teams to collect and interpret equipment-level data, identify anomalies and losses, establish digital energy baselines, assess improvement measures, and prepare results for subsequent measurement and verification.

Industrial Energy Efficiency

Strategies and practical programmes that connect energy performance with operating costs, equipment reliability, and sustainability goals.

Digital Industrial Energy Auditing

A structured, data-driven approach used by energy-audit providers and industrial enterprises to identify anomalies and losses, establish digital energy baselines, evaluate improvement measures, and prepare results for subsequent verification.

Smart Manufacturing & Industrial Digitalisation

Connecting equipment, energy, production, and operational context in live industrial environments without requiring wholesale replacement of existing systems.

Energy Intelligence & Advanced Analytics

Turning granular industrial data into decision-ready insight through performance analysis, anomaly detection, digital baselines, and the responsible use of AI-enabled analytical tools.

Operational Performance & Loss Reduction

Using energy and equipment signals to reveal hidden waste, downtime, inefficient operating modes, and practical opportunities for improvement.

Technology Strategy & Market Development

Introducing new industrial technology categories, shaping regional go-to-market and implementation models, and scaling solutions across complex B2B environments.

Energy-audit companies and professional auditors use the methodology to structure fieldwork, improve data collection and analysis, identify energy-performance deviations, and prepare evidence-based recommendations.

Industrial enterprises use it to understand equipment-level energy performance, reveal technical, organisational, and behavioural losses, prioritise improvement measures, and establish a basis for subsequent verification.

Equipment classification logic

Each monitored asset is classified across four dimensions: installed power, operational function, operating mode, and electrical-load characteristics. This classification determines measurement priority and analytical treatment.

Fit-for-purpose measurement

The methodology distinguishes between different classes of measurement equipment and connects their selection with asset characteristics, required accuracy, analytical objectives, and subsequent verification needs.

Data sufficiency before conclusions

Observation periods and data-quality requirements vary according to equipment operating modes. Measurements must satisfy defined completeness, coverage, and stability conditions before they can support an analytical conclusion.

Context before anomaly

Energy readings are interpreted against production output, shifts, schedules, operating modes, and recorded events. An explained production event is separated from a confirmed energy-performance anomaly.

Anomaly and loss taxonomy

The methodology distinguishes excess load, performance drift, idle running, out-of-hours operation, start-and-stop deviations, inter-shift variability, seasonal effects, and unexplained consumption. Identified losses are further classified as technical, organisational, or behavioural.

Digital baselines and verification

Quality-controlled equipment data is used to establish digital energy baselines and prepare a traceable package for evaluating improvement measures and subsequently verifying their effect.

Access the methodology

Request a concise methodology brief for an overview of the framework, its users, signature mechanisms, and outputs. The full methodology, including detailed operating rules and technical parameters, is available upon request.

How We Built the Energy Monitoring Market from Scratch

Andrei Kupchin reflects on the process of introducing a new category of device-level energy monitoring to the CIS market and transforming practical implementation experience into a structured methodology for industrial energy efficiency.

The Internet of Things Around the World and in Belarus: How Technology Is Transforming the Economy

Andrei Kupchin provides an expert perspective on how IoT technologies are transforming industrial operations, business models, energy management, and the wider economy.

Andrei Kupchin, “Intellectual Energy Monitoring”: Building a Business That Saves Every Kilowatt

An interview on building the energy-monitoring market in the CIS and turning equipment-level data into measurable industrial and operational improvements.