After analysing the costs of oil, rest and inrush current in a manufacturing facility, recommendations made by Waterford Institute of Technology students have saved the company 13% in energy costs. Helen Curtis and Raymond Darcy report

The manufacturing sector is one of the major contributors to high energy consumption on an international scale. Newer technologies put emphasis on energy consumption and machine efficiencies, reducing energy consumption and thereby reducing costs.

In the ideal scenario industry would introduce these technologies and adapt their facility to yield the best outcome, both financially and environmentally. However, most likely this is not the case and older machines are still in production.

It is reasonable to speculate that many facilities typically feature a series of old, higher-energy consuming machines, or a combination of new energy equipment and older machines that may be slowly being replaced. In these cases, there are significant opportunities for industrial facilities to reduce or prevent pollution and waste through the application of proven technologies in the manufacturing area, which offer finical savings as well as helping to protect the environment.

Energy-management systems aid the continuous improvement of the energy performance in an industry, but these systems can be quite costly and smaller firms may not commit to this expense – nor may it be financially feasible to implement such a system. Despite this, it is still extremely important for any manufacturing company to be aware of its energy usage.

Students in Waterford Institute of Technology considered this statement and posed the research question: can an effective energy measuring and monitoring system be designed, which can control production machines so as to reduce operational costs?

The solution itself had to be low cost and it also had to be relatively easily deployed in a production facility with both outmoded and advanced equipment. The case study was carried out in a facility that produces high volume precision components.

The computer numerical controlled (CNC) milling and turning machines to produce these components varied significantly in size, power, capability and age, as well as the production processes and cycle times. This diversity gave the students a good base on which to model results and thereby answer the question posed.

Root-cause analysis of energy usages

Using the six sigma methodologies and tools, the students determined the possible factors leading to high energy consumption. The team’s root-cause analysis established that the company had no means of knowing the energy used and potentially wasted during the machine rest times (machine in idle mode) and it is these rest times that become the main focus of the project.

A three-phase power meter was purchased and a plan derived to collect the data. Once the data was collected, the analysis began, looking for expected results and trends. With this, a number of calculations were derived to determine the feasibility of implementing this change in company protocol and calculate the expected savings.

Two areas of concern were identified and evaluated to achieve the possible overall energy savings for each machine within the manufacturing facility. The major contributor was electricity expense of a machine at rest and the second factor was slide-way oil consumption of a machine at rest.

Oil was recorded manually, as it is refilled by maintenance daily for each machine; oil is wasted during rest times as electricity is consumed to pump and heat the oil in order for the machine to be ready for production.

Power consumption is best measured and monitored with the use of power meters. A meter that recorded energy data automatically and continuously with three sensor clamps attached to the three phases of a machine was used. The meter not only measured power consumption of a machine at rest, but also the surge current of a machine.

This initial inrush of current when powering up a machine can be much greater than the steady state operating current, so it may be more expensive to power back-up a machine each time than the running costs of a machine at rest. Therefore, it was an important factor to be taken into account in the calculations.

By applying results from the three contributing factors (oil cost, rest cost and inrush current cost) to the overall cost savings equation, a decision was made to what machines would be recommended for shutdown while at rest in order to achieve financial benefits.

Deciding factors for machine shutdown

For the overall savings per hour, each machine was seen to have savings, some with high savings and many with low savings. However, the likelihood that a machine would be shut down while at rest for an hour was impractical and the number of hours a machine was at rest per week contributed to the deciding factor for shutdown.

The overall total savings per week calculations resulted in five machines being recommended for shutdown. The final saving came to a value of €2,243 per month, resulting in a reducing of 13% in the company’s monthly electricity bill.

The data demonstrated that energy efficiency could be derived from a cost-oriented control system designed on the basis of rest-time power consumption and oil consumption. However, an additional important factor proved to be power surge in the case study. It was evident that for machines with higher rest periods, the potential savings were significant, indicating that production facilities in transition from old to newer equipment could make significant savings.

These machines being shut down while at rest have high rest costs and are at rest a large portion of their time. High rest costs and large portions of rest hours are linked to the older machines because not only are they inefficient, but they are only in production for a few hours in the week. For many operations, newer machines have replaced these machines for long periods.

Prior to this study, the company did not have any realisation of whether or not these machines were costing it money whilst they were at rest. Furthermore, there was the possibility that shutting down the machines and restarting them later would prove to be more expensive to the company rather than leaving the machines on.

This study showed that the control of production equipment whilst both in operation and at rest can yield significant potential energy savings in production settings, especially where there is a mix of newer technologies and older, less energy-efficient systems.

The findings suggest that such an analysis is very useful as a cost-oriented measure. The solution required little upfront capital investment in spite of the immediate savings available.

Helen Curtis and Raymond Darcy, two undergraduate students from Waterford Institute of Technology, undertook an industrial-based project as part of the college’s BEng in Manufacturing Engineering course. The project became the subject for an academic paper to be written where it was accepted and published with Elsevier, the International Federation of Automatic Control Publisher and later presented at the IFAC International Conference on International Stability, Technology and Culture by project supervisor Mary Doyle-Kent.

The industrial-based project meant the students were introduced into the manufacturing environment and, seeing as WIT is situated in the heart of Waterford’s industrial sector, staff have taken this and built a connection with the local manufacturing industries to present students to potential future employers. Project client Seamus Power led the project from the business side and saw the need for an effective energy measuring and monitoring system in industry and, with help from the students and lecturers of WIT investigated, developed and implemented a cost-efficient solution.

BEng Ordinary Degree in Manufacturing Engineering in WIT (WD208) 2015 class (click to enlarge) O'RiordanMech
The manufacturing sector is one of the major contributors to high energy consumption on an international scale. Newer technologies put emphasis on energy consumption and machine efficiencies, reducing energy consumption and thereby reducing costs. In the ideal scenario industry would introduce these technologies and adapt their facility to yield the...