A methodology based on the manufacturing processes aspect can be developed from energy losses during operation time. This approach considers energy losses due to lack of skills, materials, tools and so on. However, there are other hidden energy losses pre-operation which are vital to measure to determine equipment energy effectiveness. The manufacturing processes aspect should also identify pre-operation energy losses during time losses due to management, organisation, personnel, and inputs and so on. This aspect monitors the actual energy performance of a machine relative to its equipment settings under optimal manufacturing processes.
As previously mentioned, there is also an essential need to develop a new broad model to cover the energy aspect of equipment energy effectiveness. This approach considers thermodynamic efficiency of the process to minimise energy losses due to thermodynamic inefficiencies. If there are technical constrains to identify or address these inefficiencies, Best Practice Energy Per Unit (BEPU) can alternatively be applied.
Combustible fuels accounted for 67.3% (of which: 65.1% were fossil fuels) of total world gross electricity production in 2016 (21). The energy aspect should also cover the types of energy i.e. renewable or non-renewable to tackle the major problem of reducing GHG emissions. This aspect monitors the actual energy performance of a machine under optimal energy usage. As shown in Figure 1, the TEEE model is a comprehensive framework that covers all equipment, manufacturing processes and energy aspects. TEEE is a measure of how efficiently equipment consumes energy compared to its full potential.
The level of comprehensiveness can be a possible serious impediment to apply a total energy effectiveness methodology especially in small and some medium size firms. TEEE, as a novel methodology, is designed to solve the problem. The technical data provisions originated from OEE measurement can be used as a solid base to develop an appropriate TEEE measurement system.
Overall equipment effectiveness (OEE), as introduced by Nakajima (1988), is seen to be the fundamental way of measuring equipment efficiency and has been extensively accepted as a major quantitative tool for measuring the productivity of manufacturing systems (22). It is the essential measure of total productive maintenance (TPM) and has become one of the most common used metrics for operations. The concept of OEE is being used increasingly in industry because it quantifies efficiency into a simple number, while revealing the actual effectiveness of a machine.
A high number of manufacturing companies have already developed the appropriate IT structure to collect and analyse data to measure OEE. The system can be simply adapted to meet the requirements of TEEE measurement. As shown in Figure 2 that structured data framework facilitates measuring TEEE. All tiers of both equipment and manufacturing aspects can be integrated to develop four stages of pre-operation, gross operation, net operation and value operation. As mentioned later and shown in Figure 4, all energy factors for gross operation, net operation and value operation can be measured via obtaining results of OEE calculations along with access to the Power consumption during Operation (POPE) quantity.
The energy loss analysis scheme during pre-operation time
A set of manufacturing surroundings affect the energy performance of equipment during pre-operation time. Anvari et al (2010) show that there are considerable time losses before loading time (23). As shown in Figure 3, these energy losses can be categorised under eight headings:
1- Energy consumption during Non-Scheduled Time (NST) related to production consists of: all consumed energy during time spent on any disruption to the production schedule, time spent on carrying out current orders, general preparation and basic maintenance such as cleaning and lubrication. It can be calculated as follows:
Energy consumption during NSTPro = NSTPro × PNST
Where:
PNST= Power consumption during NST
2- Energy consumption during Non-Scheduled Time (NST) related to personnel consists of: all consumed energy during time losses because of shortage of labor due to daily shop floor meetings, and training. It can be calculated as follows:
Energy consumption during NSTPer = NSTPer × PNST
3- Energy consumption during Non-Scheduled Time (NST) related to organisation consists of: all consumed energy during non-operational time due to shift changing, and unscheduled time for holidays and night shifts. It can be calculated as follows:
Energy consumption during NSTOrg = NSTOrg × PNST
4- Energy consumption during Non-Scheduled Time (NST) related to management consists of: all consumed energy during time spent on precautionary periods. It can be calculated as follows:
Energy consumption during NSTMng = NSTMng × PNST
5- Energy consumption during non-scheduled time related to inputs consists of: all consumed energy during non-operational time due to lack of material, electricity and utilities such as water. It can be calculated as follows:
Energy consumption during NSTInp = NSTInp × PNST
6- Energy consumption during Improvement Time consists of: all consumed energy during time spent on R&D, and activities for upgrading plant, equipment and process which need no operation of machines. It can be calculated as follows:
Energy consumption during improvement time= Improvement Time × PIMP
Where:
PIMP= Power consumption during Improvement Time
7- Energy consumption during engineering time consists of: all consumed energy during repair time other than appointed time for preventive maintenance and other regular planned maintenance tasks. It can be calculated as follows:
Energy consumption during Engineering Time= Engineering Time × PENG
Where:
PENG= Power consumption during Engineering Time
8- Energy consumption during Planned Maintenance Time can be calculated as follows:
Energy consumption during Planned Maintenance Time = Planned Maintenance Time × PMAI
Where:
PMAI= Power consumption during Planned Maintenance Time
Hence Energy Consumption during Time Losses Before Loading (TLBL) can be calculated as:
Energy Consumption during å TLBL= (å NST) × (PNST) + (Improvement Time) × (PIMP) + (Engineering Time) × (PENG) + (Planned Maintenance Time) × (PMAI)
Where:
å TLBL=The sum of all Time Losses Before Loading
=å NST + Improvement Time + Engineering Time + Planned Maintenance Time
and
å NST= NSTPro + NSTPer + NSTOrg + NSTMng + NSTInp
Figure 3 summarises the energy loss analysis scheme during pre-operation time.
The energy loss analysis scheme during operation time
A set of machine conditions along with manufacturing processes affect the energy performance of equipment during operation time. Tajiri and Gotoh (1992) classify major time losses during operations into six groups. Breakdown losses, setup and adjustment losses are downtime losses used to determine a true value for the availability of a machine. The third and fourth losses, including minor stoppage and reduced speed losses, are known as speed losses. They are used as a measure of performance rate of a given machine. Rework and yield losses are defined as quality losses that determine the quality rate for the equipment (24). As shown in Figure 4, the energy losses during operation time can be categorised under three headings:
I- Energy Losses during Gross Operation
Breakdown losses are caused by equipment requiring maintenance. One example is the downtime when labour and spare parts are needed to repair the equipment. Setup and adjustment losses are caused by changes in operating circumstances, for example changes in the beginning of production runs or commencement at each shift. These losses include downtime for setup, start-up, and adjustment. Energy consumption during downtime Losses i.e. breakdown, setup and adjustment losses are used to determine Energy-Availability (EA).
II- Energy Losses during Net Operation
Minor stoppage losses are caused by events such as the machine jamming, halting, and idling. Normally a minor stoppage of more than 10 minutes is considered as a breakdown even if no damage has happened to the equipment. Speed losses are caused by decreased operating speed. These losses are calculated on the basis of the ratio of theoretical to actual operating speed. Energy consumption during speed losses i.e. idling, minor stoppage and reduced speed losses are used to determine Energy-Performance rate (EP).
III- Energy Losses during Valuable Operation
Quality and rework losses are caused by defective products manufactured during normal production. Yield losses are caused by unused or wasted raw materials during the early stages of production from machine start up to stabilisation. Energy consumption during quality losses i.e. start up and production rejects are used to determine Energy-Quality rate (EQ).
The energy loss analysis scheme based on thermodynamic efficiency
Thermodynamic methods provide a measure of inefficiencies within a process and accordingly the maximum theoretical improvement potential. Although it is accepted this optimal limit will not be reached in practice, it can still be instructive in showing where differences may arise (5). Thermodynamic analysis can outline the extent of energy inefficiencies within the constraints of the existing process along with potential improvements.
As previously mentioned, the energy intensity of most industrial processes is at least 50% higher than the theoretical minimum determined by the laws of Thermodynamics. Motor systems consume about 65% of electricity in industry. Measures can be aimed at improving the aerodynamics of the motor, its windings and applying higher quality magnetic steel. For example, scrap preheating and oxygen injection in steel industry or better membranes for separation and more selective catalysts for synthesis in chemical industry can decrease energy consumption (3). Energy Consumption due to thermodynamic losses are used to determine Energy-Thermodynamic efficiency (ET).
The energy loss analysis scheme based on non-renewable energy consumption
According to ETP 2015, among energy end uses, heating and cooling systems offer significant potential for decarbonisation that so far have been mostly untapped. They were responsible for 30% of global carbon dioxide (CO2) emissions in 2012 as 70% of heating and cooling demand were relying on fossil energy sources. Broad application of energy efficiency and switching to low-carbon energy sources can lead the fossil share to below 50% by 2050 with renewables (including renewable electricity) covering more than 40% of heating and cooling needs. Direct and indirect CO2 emissions linked to heating and cooling would fall by more than one-third by 2050 (7).
It is vital to improve energy efficiency; however, there is growing concern about global warming, public health, the exhaustion of fossil fuels and energy price stability. This signifies that the suggested model should involve this element of sustainability. A more effective CO2 strategy should concentrate on shifting to renewables. Other substantial benefits such as reliability and resilience and Jobs and other economic benefits can also be derived from renewable energy use. The energy revolution scenario indicates that renewable energy can meet more than 80% of the world’s energy demands by 2050 (25).
Some organisations may leave this energy factor and focus on other losses. They can add this factor when they are able to make adequate provisions against non-renewable sources. Non-renewable energy consumption is considered to determine Energy-Renewable rate (ER).
Total Equipment Energy Efficiency (TEEE) structure
Based on the TEEE methodology and the above loss analysis schemes, TEEE structure can be defined.
As shown in Figure 4, six elements of TEEE are defined as follows:
EB = Energy Consumption during Pre-Operation Time / Energy Consumption during Calendar Time
= (Energy Consumption during Calendar Time - Energy Consumption during Time Losses Before
Loading) / Energy Consumption during Calendar Time
=1 – (Energy Consumption during Time Losses Before Loading / Energy Consumption during
Calendar Time)
= 1 - [(å NST) × (PNST) + (Improvement Time) × (PIMP) + (Engineering Time) × (PENG) + (Planned
Maintenance Time) × (PMAI)] / Energy Consumption during Calendar Time
EA = Energy Consumption during Operation Time / Energy Consumption during Pre-Operation Time
= [(Pre-Operation Time – Down time) × POPE] / (Energy Consumption during Calendar Time –
Energy Consumption during Time Losses Before Loading)
= [(Pre-Operation Time – Down time) × POPE] / [(Energy Consumption during Calendar Time –
[(å NST) × (PNST) + (Improvement Time) × (PIMP) + (Engineering Time) × (PENG) + (Planned
Maintenance Time) × (PMAI)]]
Where:
POPE= Power consumption during Operation
EP = Energy Consumption during Net Operation Time / Energy Consumption during Operation Time
= (Cycle time per unit × Processed amount × POPE) / [(Pre-Operation Time – Down time) × POPE]
= (Cycle time per unit × Processed amount) / (Pre-Operation Time – Down time)
EQ = Energy Consumption during Valuable Operation Time / Energy Consumption during Net
Operation Time
= Cycle time per unit × (Processed amount – Defects amount) × POPE) / (Cycle time per unit ×
Processed amount× POPE]
= (Processed amount – Defects amount) / Processed amount
= 1 – (Defects amount / Processed amount)
ET = Energy Consumption during Thermodynamically Efficient Process / Energy Consumption during
Valuable Operation Time
= (Energy Consumption during Valuable Operation Time – Energy Consumption due to
Thermodynamic Inefficiencies) / Energy Consumption during Valuable Operation Time
= 1 – (Energy Consumption due to Thermodynamic Inefficiencies) / Energy Consumption during
Valuable Operation Time)
ER = Renewable Energy Consumption/ (Renewable Energy Consumption + Non-Renewable Energy)
= Renewable Energy Consumption during Calendar Time / Energy Consumption during Calendar
Time
Hence TEEE can be calculated as given:
TEE= EB × EA × EP × EQ × ET× ER
As earlier mentioned, some manufacturing firms may leave ER and focus on other losses. They can add this factor when they are ready. TEEE without considering Renewables can be calculated as given:
TEEE= EB × EA × EP × EQ × ET
All elements of TEE are summarised in Figure 5.