User talk:Michael Alexander Missalla

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Perficiency[edit]

Perficiency is a parameter used in industrial plants to define the efficiency of a process. The Perficiency parameter is the combination of Overall Equipment Effectiveness (OEE) and Total Effective Equipment Performance (TEEP). OEE considers availability, plant performance and product quality, while TEEP additionally accounts for loading. However, these indicators, which were originally developed for assessment of production machines with non-continuous processes, do not give a clear indication on how efficient the process actually is run.

Perficiency = TEEP x Process Efficiency

Calculations for Perficiency[edit]

OEE and TEEP[edit]

Overall equipment effectiveness[edit]

The term OEE was coined by Seiichi Nicky Jamima. It is based on the Harrington Emerson way of thinking regarding labor efficiency. The generic form of OEE allows comparison between manufacturing units in differing industries. It is not however an absolute measure and is best used to identify scope for process performance improvement, and how to get the improvement. OEE measurement is also commonly used as a key performance indicator (KPI) in conjunction with lean manufacturing efforts to provide an indicator of success.

OEE [%] = Availability x Performance x Quality

Total effective equipment performance[edit]

TEEP is a closely related measure which quantifies OEE against calendar hours rather than only against scheduled operating hours. TEEP measures OEE effectiveness against calendar hours, i.e.: 24 hours per day, 365 days per year. A TEEP of 100% means that the operations have run with an OEE of 100% 24 hours a day and 365 days a year (100% loading).

TEEP [%] = Loading x OEE

Loading[edit]

The portion of the TEEP Metric that represents the percentage of total calendar time that is actually scheduled for operation. The Loading portion of the TEEP Metric represents the percentage of time that an operation is scheduled to operate compared to the total Calendar Time that is available. The Loading Metric is a pure measurement of Schedule Effectiveness and is designed to exclude the effects how well that operation may perform

Loading [%] = Scheduled Time / Calendar Time

Availability[edit]

The portion of the OEE Metric represents the percentage of scheduled time that the operation is available to operate. Often referred to as Uptime. The Availability portion of the OEE Metric represents the percentage of scheduled time that the operation is available to operate. The Availability Metric is a pure measurement of Uptime that is designed to exclude the effects of Quality, Performance, and Scheduled Downtime Events.

Availability [%] = Available Time / Scheduled Time

Performance[edit]

The Performance portion of the OEE Metric represents the speed / capacity at which the Plant / Equipment runs as a percentage of its designed speed / capacity. The Performance Metric is a pure measurement of speed/ capacity that is designed to exclude the effects of Quality and Availability.

Performance [%] = Actual Rate / Standard Rate Performance [%] = Actual Production / Name Plate Production Performance [%] = Actual Capacity / Name Plate Capacity

Quality[edit]

The portion of the OEE Metric represents the Good Units/Product produced as a percentage of the Total Units /Product. Commonly referred to as First Pass Yield. The Quality Metric is a pure measurement of Process Yield that is designed to exclude the effects of Availability and Performance

Quality [%] = Good Units / Total Units Quality [%] = Good Product (within Specification) / Total Product produced

Process Efficiency[edit]

Energy loss[edit]

The portion of Process Efficiency Metric which references the unit/plant/euqipment operated in its energy optimum

Energy Loos [%] = Optimium Energy consumption / actual Energy consumption.

Energy consumption calculates for fossil as well as electrical energy. Electrical energy will be multiplied by its respective energy conversion efficiency and added to the fossil energy. Increased energy consumption leads to reduced process efficiency;

Raw material loss[edit]

The portion of Process Efficiency Metric which references the unit/plant/euqipment operated in its optimum with respect to raw material losses

Raw material Loos [%] = actual raw material usage / Optimium raw material usage.

Raw material is entered in the process and then either transformed, separated, concentrated etc. However certain percentage of the raw material can even in an optimal usage not been transformed, separated or concentrated. A deviation from this optimum will be captured in this factor. An insufficient recovery of the product from the feed material indicates a reduction in raw material utilization;

Other utility loss[edit]

In this category the consumption of diverse support utilities is gathered.

The portion of Process Efficiency Metric which references the unit/plant/euqipment operated in its optimum with respect to other utility losses

Other utility Loos [%] = actual other utility usage / Optimium other utility usage.

Increased consumption of other utilities besides energy (such as water, nitrogen, soda, start-up diesel etc.) reduce process efficiency;

Environmental loss to soil, air, water or waste[edit]

In this category all regulated emissions to the environment are gathered and compared to their emission limits. If they are below the limits the factor is set to 100%.

The portion of Process Efficiency Metric which references the unit/plant/euqipment operated within its regulative limits.

Increase in regulated emissions to the environment reduce process efficiency.

References:[edit]

V. Palanisamy, Jose Ananth Vino: Implementing Overall Equipment Effectiveness in a Process Industry, Indian Journal of Science and Technology, Vol 6, 06/2013, Print ISSN: 0974-6846

Capstone Metrics LLC: Overall Equipment Effectiveness (OEE) – A General Discussion with Calculation Methods, 2011 www.oee.com/oee-six-bis-losses.html, accessed 2017, July 20th

M. Missalla, L. Perander, S. Haus and N. Anastasijevic, Further Optimization of Product Quality and Plant Performance in the Calcination Process by Utilizing Digital Tools, Travaux 46, Proceedings of 35th International ICSOBA Conference, Hamburg, Germany, 2 – 5 October, 2017, pp 393 – 406.

M. Missalla, L. Perander, S. Haus, N. Anastasijevic and S. Horn, How digitalization can further improve plant performance and product quality Outotec Pretium Advisory tool for alumina calcination, Light Metals TMS 2018, pp XX-XX.