Energy use affects every saleable unit leaving your plant. Electricity, natural gas, compressed air, heating, cooling, process equipment, and production lines all add to manufacturing energy costs, whether those costs are visible in a work order or buried in facility overhead.
For Canadian and North American manufacturers, variable electricity rates, demand charges, and production constraints make energy cost per good unit an important operating metric. Comparing energy consumption across work orders helps managers identify which products, production runs, and work centres use more energy to produce the same quantity of acceptable output. The next step is to connect those differences with actual production time, downtime, and rejected units.
Measure Manufacturing Energy Consumption Per Good Unit
A facility electricity bill shows total consumption, but it cannot explain why one run of a product used more power than another. That answer appears when energy readings are matched with production records, including work orders, work centres, run times, acceptable output, rejects, and idle periods.
The basic calculations are straightforward:
- Energy consumption per good unit = kWh consumed during a production run ÷ acceptable units produced
- Energy cost per good unit = total energy cost for the production run ÷ acceptable units produced
- Where a direct electricity rate applies: total electricity cost = kWh consumed × applicable electricity rate
- Rejected units should be recorded separately because they consume production energy but do not contribute to acceptable output.
Direct measurement gives you the clearest view. Interval meters, sub-meters, machine-level electricity meters, and compatible monitoring devices can capture consumption for a line, machine, or defined production period. These readings should be matched with the start and finish times of the relevant Work Orders, along with the quantity produced and the number of rejected units. This creates a consistent basis for calculating energy consumption and cost per acceptable unit. We recommend recording readings at the beginning and end of a run, then comparing them with the related work order duration, quantity produced, rejected quantity, and periods when equipment was powered but not producing.
When direct readings are unavailable, you can begin with estimated allocations based on machine runtime, rated equipment load, or work centre operating hours. These estimates can support early energy efficiency in manufacturing reviews, but they should be clearly labelled as allocations rather than measured electricity consumption. Shared items such as demand charges, delivery fees, and facility-wide heating or cooling also need a documented allocation method that is applied consistently.
Find Energy Waste in Production Data
Higher energy cost per unit often points to an operational question worth investigating. Equipment can keep drawing power while waiting for materials, operators, inspections, approvals, changeovers, repairs, or the next scheduled task. Longer work order durations and unplanned downtime can raise manufacturing energy consumption even when output remains flat.
Rejected units have a similar financial effect. The run may consume the same amount of energy, but that energy is spread across fewer acceptable products. A rise in energy cost per unit does not automatically mean a machine is failing. It may reflect lower throughput, a product specification change, more setup time, a scheduling issue, or a larger number of rejects.
To make the data useful, we suggest reviewing energy per unit across several views:
- Product and product family
- Work centre, machine, and production line
- Shift or operator team
- Individual work order and production period
- Planned duration compared with actual run time
These comparisons add a financial dimension to downtime and preventive maintenance discussions. Idle equipment, compressed-air losses, excess heat, slow cycle times, and declining equipment condition can all show up in a measured increase in energy cost per acceptable unit.
Connect Production Records to Energy Context
Odoo 20 Manufacturing provides the production context for energy analysis. Manufacturing Orders identify the products and quantities produced, while Work Orders record the operations, work centres, and actual durations involved. These records help managers identify which production runs to compare with external energy readings.
Match meter readings to the relevant Work Orders using the production dates, work centre or machine, operating time, and quantity of acceptable units. This requires compatible metering equipment and an integration or reporting process that connects energy readings with Odoo production records.
Odoo 20 calculates manufacturing costs using component quantities and costs, work centre operating costs, and employee labour costs. The estimated MO Cost uses the per-employee rate configured on the Work Centre. Actual labour costs use the Hourly Cost recorded on each employee's profile, while actual component consumption and recorded operation durations can also affect the final cost. The MO Overview displays both MO Cost (estimated) and Real Cost (actual). Before production starts, these values are the same. During production, actual component consumption, operation durations, and employee hourly costs can cause them to differ. Once the Manufacturing Order is completed, the MO Cost updates to match the Real Cost.
These manufacturing cost figures do not measure electricity or gas consumption. Actual energy readings must come from external meters or monitoring devices. For a broader explanation of how production inputs and operational costs affect manufacturing margins, see our guide to [Costing Errors in Manufacturing: How Leading Teams Fix Them].
Standard Odoo 20 Manufacturing does not automatically collect electricity, natural gas, or compressed-air consumption from facility meters and assign those readings to individual Work Orders. Odoo IoT supports compatible physical devices such as digital calipers, depth gauges, measuring tools, scales, and cameras. However, these examples do not establish standard compatibility with industrial energy meters. Connecting electricity, gas, or compressed-air meters to production records may require an external monitoring platform, compatible hardware, an API integration, or custom reporting.
An IoT Box subscription is required for production use of Odoo IoT systems. The project scope should also confirm hardware compatibility, the target Odoo edition, available applications, data-collection requirements, and reporting limitations.
Turn Energy Data Into Operational Decisions
Consider this hypothetical Canadian example. A production line starts a run with a sub-meter reading of 12,000 kWh and ends at 12,480 kWh. The line consumed 480 kWh. At a hypothetical electricity rate of $0.14 per kWh, the measured electricity cost for the run is $67.20.
If the run produces 1,200 acceptable units, consumption equals 0.40 kWh per unit. Energy cost equals $0.056 per acceptable unit. Linked to the related Work Order, this figure becomes a measurable part of that product run’s performance.
Now compare a second hypothetical run of the same product. The line consumes 580 kWh and produces 1,050 acceptable units. At the same $0.14 rate, electricity cost is $81.20, or about $0.077 per acceptable unit. The difference should trigger investigation, not assumptions.
Longer operating time, idle equipment during material delays, slower cycle times, additional rejects, maintenance concerns, or production scheduling changes could each contribute. Natural Resources Canada provides broader energy-efficiency resources, while your own production data shows where to focus attention inside the facility.
Build a Reliable Energy-to-Production View
You do not need to begin with a facility-wide transformation project. Measuring one high-consumption line, machine, or work centre and matching its readings to output can provide a credible starting point for energy management.
A dependable view needs reliable meter readings or documented estimates, production start and end times, Work Order or Manufacturing Order identifiers, good output, rejected quantities, applicable energy rates, and a consistent method for shared costs. Manufacturing systems can supply valuable production, work order, work centre, and cost context, while external monitoring, integrations, and custom reporting can connect that context to actual energy consumption. Over time, this gives your team a clearer basis for reviewing bottlenecks, maintenance priorities, scheduling decisions, and unit margins.
Turn Energy Data Into Better Unit Economics
Kodershop helps manufacturers connect operational context with the energy data needed to make confident cost decisions. Learn how energy management in manufacturing can support clearer cost-per-unit reporting and more informed production planning. When you are ready to assess the systems, integrations, or reporting your operation needs, contact us to discuss your requirements.