With the cost of energy continuing to escalate many manufacturing business are considering energy as a cost of production, rather than an overhead. Subsequently they are investing time and resource to reduce consumption. In fact a recent survey undertaken by EEF showed that energy and waste reduction are the most common environmental strategies adopted by manufacturing businesses[i].

Figure 1 – The increasing cost of energy

The same survey showed that the majority of manufacturers were applying lean techniques which delivered tangible benefits. Furthermore, it is probably not surprising to know that lean companies are greener than their counterparts who have not yet adopted the same techniques.[ii]

This article will explore the effectiveness of integrating energy optimisation into lean activities. It will present that lean activity is not as effective without taking into consideration energy and likewise, that energy reduction programmes are less effective and too narrowly focused without the structure of lean.

How can lean reduce energy?

“Value is created when an activity transforms the “form, fit, or function” of the product, the customer is willing to pay for this change and it is done right first time. Everything else is non-value adding (or waste) and should be reduced and eliminated”

The key principals of value and waste in lean apply directly to energy. Energy, like all other resource, can be associated with the value adding steps (e.g. a machine cutting a component) and with the non-value adding. From the studies we have undertaken the time that energy is being consumed in a non-productive state is often proportionally higher than when adding value. This supports the laws of lean in the need to reduce or eliminate this waste first, before focussing on the value adding activity..

To provide further clarity, the non-value adding activities (or wastes) in lean are also broken down into ‘the seven deadly wastes’, all of which directly apply to energy usage. These can be seen below.

Lean Waste	Related Energy Wastes
Overproduction	Energy consumed in operating equipment to make unnecessary products.
Inventory	Energy used to heat, cool and light inventory storage space.
Transportation and Motion	Energy used to transport product (e.g. conveyors, forklifts etc.) More energy required to heat, cool and light areas where work in progress is moved.
Defects	Energy consumed in making defective products. Energy for rework and repair (in operation and in heating, lighting and cooling).
Overprocessing	Energy consumed by equipment whilst it over processing (often product and process enhancements that are not required by the end customer). Energy waste by utilising equipment that is not the right size for the task.
Waiting	Wasted energy from heating, cooling and lighting production downtime. Wasted energy whilst a machine is waiting for work.

Table 1 – The 7 Deadly Wastes and Related Energy Impact (adapted from[iii])

Let’s study an energy profile of a working machine in Figure 2. The differing energy levels mapped on the graph show its operating state, the highest being when it is producing followed by on but not producing, standby and off. The percentage of time for each state is illustrated in the pie chart (producing 47%, on but waiting 27%, standby 22% and off 5% of the time).

Figure 2 – Example of and Energy Profile of a Machine

Table 2 explores the specific states of the machine in more detail and gives some examples of the potential issues or wastes associated with each state. Examples of some of the specific lean tools designed to resolve the specific issues or wastes are then listed.

Table 2 – Energy States, issues, wastes and lean tools

So what does this prove? The complementary nature of energy reduction and lean tools and techniques are clearly demonstrated. In practice, using these tools as part of a company’s improvement activity delivers tangible, sustained results. However, energy improvements implemented in isolation may have an undesired effect elsewhere. Therefore, energy as a component of a number of measures used in lean ensures that any improvements are optimal rather than just focused on one area at the expense of another.

For example, an oven in a bakery should, from an energy perspective, be turned off between batches. However when talking lean, if to heat up the oven increases set up times, which in turn increases batch sizes this cannot be a viable solution. But, if also assessing the cost of energy  we have often found ovens can be reduced by a few degrees without an impact on set up times. By factoring the two metrics together, an even more optimum solution has been found.

Furthermore structured analysis through lean tools (like process and value mapping) integrated with a balanced set of data will show where energy improvements can be made and measures optimised.

Figure 3 – Energy Integrated into a Value Stream Map adapted from[iv]

How can energy optimisation help lean activities

In our introduction, we mentioned a study in the US that showed companies who embraced lean manufacturing were also by nature more greenii. Therefore even without considering energy, lean interventions in the most case have a positive impact on energy. So, it seems that lean engineers and projects are omitting the positive impact they have on energy costs even though there is a high probability their actions have reduced or optimised energy consumption.

But the benefits go even further than simply capturing this additional benefit. Lean, and in fact any improvement technique, needs to be driven by robust data and analysis, if you don’t measure it, how do you know you have improved it? More manufacturing companies are finding that to reduce energy it needs to be done from the bottom up, to understand where energy is being consumed, and where specific areas are inefficient. There is a realisation that even smart meters and half hourly bills do not provide granularity. Therefore the only practical solution is to monitor individual machines or areas, which is actually relatively inexpensive. Energy data, in return, can be used to drive a number of established lean techniques.

Let’s take the energy data we used in the previous section and understand how it directly helps:

1. Shows where processes are not balanced (Line Balancing)
2. Shows where improvements should be focused to release capacity (Theory of Constraints).
3. Measure the efficiency and effectiveness of a machine (OEE)

Firstly looking at Line Balancing and Theory of Constraints, again we can take the productive time from our previous example and put this with the productive time of the other components of the process (Figure 4).

Figure 4 – Using Energy Data for Line Balancing and Constraint Identification

You can see in Figure 4 that the line is not balanced and therefore parts of the process have capacity and others will be constraining total throughput. The energy data can therefore be used to work on balancing the line.

As you can see energy data will help identify the true constraint in an operation but more powerfully when linked with the overall profile (shown opposite) shows where capacity is actually available. Therefore to undertake the first and simplest step in Theory of Constraints, you can understand how much of an opportunity and capacity will come from exploiting or milking the constraint.

The next example uses energy data to support the measurement of the effectiveness and efficiency of a machine. Overall Equipment Effectiveness (OEE) is a hierarchy of metrics which evaluates and indicates how effectively a manufacturing operation is utilized. Figure 5, shows how energy data from a manufacturing process or machine gives accurate data on its availability. Again without the energy data, capturing availability can be often time consuming and inaccurate.

Figure 5 – Using Energy Data for OEE

Summary

With energy costs increasing more systemic and proved mechanisms for improvements need to be employed. Lean has well established tools and techniques that will deliver energy savings and will ensure that any energy focused improvements are not at the expensive of other important business metrics.

By not including energy within lean improvement strategies and programmes, companies are not only often missing additional benefits but also some crucial data that can identify valuable improvement opportunities and where to prioritise focus.

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[i] Measure Performance, Environmental Survey 2009, EEF, January 2010

[ii] Lean Manufacturers’ Transcendence to Green Manufacturing, Bergmiller and McCright

[iii] Lean, Energy and Climate Toolkit, Achieving Process Excellence Through Energy Efficiency and Greenhouse Gas Reduction, EPA

[iv] The Lean and Environment Toolkit, EPA