The cycle time of a component is 6 min/part one expects 70 parts in 7 hours (one shift). Do we actually get 70 good parts in every shift? This question if asked to most production engineer, the answer is no and the number maybe anywhere between 50 and 70. Why is this so? The reasons are many, and can be classified under three heads.

• Availability
• Performance
• Quality

Availability or Availability Efficiency (Ae) is defined as to what extent is asset (machine, equipment) available for production.

Performance or Performance Efficiency (Pe ) is defined as to what extent is asset performance compared to rated performance.

Quality or Quality Efficiency (Qe) is defined as to what extent quality is produced as compared to rated quality.

Please note the words rated in italics in the definitions to which we will return a little later.

Availability

The formula for calculating Availability (Ae) is Available Time/ Loading Time where Available Time is (Loading Time – Down Time). Here Loading Time is the time in a day/ shift after accounting for breaks granted by the management, for example, lunch and tea breaks or personal time. Illustrating this with an example, in a day of 24 hours, if 30 min is provided for lunch/ dinner break and two tea breaks of 15 min each in each shift, the Loading Time would be 24 – 1.5 (lunch breaks in 3 shifts) – 1.5 (tea breaks in 3 shifts) would be 21 hrs. Now during the day there is a set up change of 60 min and maintenance of 30 min, then the Down Time is 1.5 hrs and the Availability (Ae) is (21-1.5)/21 = 92.85% or 93%

Down Time could be due to many reasons including set up change time, breakdown maintenance time, preventive maintenance time, chip removal time, coolant change time, tool change time, time lost due to no power or no tool or no operator or no work, time lost as machine is stopped for inspection or process problem or fixture problem, time lost due to new part development and so on. All time lost due to machine stoppage exceeding 10 min is captured under Down Time and affects Ae.

If in any company Ae is below 90%, one can drill down various Down Times, carry out a Pareto Analysis and determine which ones contribute to 80% of Down Time and then work to reduce them. For example if Set up time is a major contributor, one can use SMED principles to reduce it. If breakdown maintenance is a key contributor then autonomous maintenance is an approach to reduce it. Thus an action plan can be prepared to attack the Down Time after a thorough Why Why analysis.

Performance

The formula for Performance Efficiency (Pe) is (Parts produced * Actual cycle time)/ Available Time. Referring to our earlier example, against the expected 70 parts only 65 parts were actually produced in the 7 hr shift. Let us assume that there was no Down Time in this shift. In this case the cycle time is 6 min per part and the Pe would be 65*6/420 = 92.85% or 93%.

To analyse Performance Efficiency better it can be broken down further into two factors i.e. idle or minor loss and speed loss. Speed loss is the ratio of rated cycle time/actual cycle time. It is a measure to determine to what extent a process has deteriorated from its rated condition or ideal condition. The ideal condition is when everything is ideal, i.e. machine is new, raw material has the correct composition and machining allowance, cutting tools are sharp, operators are skilled in using the machine and well trained, and process is optimized. Production is lost if these ideal condition is lost. Even if the rated cycle time is maintained there are minor stoppages for example, an insert has to be indexed, a tool offset has to be given, a chip has to be removed during part loading, etc. Each of these stoppages are below 10 min and are not accounted in Ae but in Pe. Idle or minor loss formula is Parts produced*rated cycle time/ Available Time. Pe can now be rewritten as Pe = Idle loss*speed loss = (Parts produced*rated cycle time/ Available Time)*(rated cycle time/actual cycle time)

Performance is reduced for various reasons leading to less parts produced due to frequent change in process, long inspection time during which machine is idling, cleaning time, fetching tools or fixtures or material from another location, unoptimised part clamping/ unclamping time, inconsistent incoming material, variable manual operation time, low cutting parameters due to wear and tear of machine and many more reasons. The lost time is less than 10 min for each occurrence else it would be accounted in Ae. If Pe, Speed Loss and idle or minor loss is found less than 90%. one can drill down various losses, carry out a Pareto Analysis and determine which ones contribute to 80% and then work to reduce them.

Quality

The formula for Quality Efficiency (Qe) is (total parts produced – non confirming parts)/ total parts produced. Continuing with the earlier illustration if 3 parts were non confirming i.e. including scrap and rework, then the Qe = (65-3)/ 65 = 95.38% or 95%

The most important reasons for a low Qe would be lack of process capability. This leads to scrap as well as rework. Often this is a result of lack of control of inputs such as material, tools, fixtures, machine and process. Poor maintenance of machine can also lead to a lower Qe.

The Overall Equipment Effectiveness or OEE is a product of the three factors: Ae * Pe * Qe. In our example it would be 93%*93%*95% = 82%. This clearly shows that when manufacturing engineers talk about efficiency and quote figures of 85 to 90% in reality they may not be achieving it as it could be Ae or Pe or Qe alone and not the product.

One must have noted that both in Pe and Qe, we are considering the rated or ideal condition, i.e. the rated cycle time and rated conformance in quality (100% conformance to quality standards).

For an owner of a company, there is cost of money. This is the interest paid to a bank or financial institution on borrowing money, or the interest a promoter would earn if he were to invest his capital somewhere else. In either case interest is calculated on the basis of 365 days*24 hours. Therefore OEE should ideally be calculated on the same basis, i.e. 365 days*24 hours. In our example we calculated Loading Time as 24hrs less breaks allowed by management and arrived at 21 hrs. If one were not to do so and take 24 hrs itself as Loading Time, one would get a more correct picture of utilizing ones equipment effectively. The loss of 3 hrs is a Management Loss because management is unable to utilize the equipment during breaks. This is captured by a metric Me.

Total Effective Equipment Performance (TEEP) which is a product of Me*Ae*Pe*Qe. In this case Me is Loading Time/ 24hrs. In our example it would have been 21/24 = 87%. Now if OEE was 82% the TEEP would be 87%*82% = 71%. This shows that there is a potential capacity to improve productivity by as much as 29%.

The National Productivity Summit 2015 at Gurgaon on 20 -21^st Nov, showcases through its case studies and keynote addresses how teams have significantly improved productivity at their workplace. Various tools have been effectively used by these teams to discover the hidden losses in their process and they have found innovative solutions to their challenges thrown to them by their customers. This “out of the box” thinking is very important for these companies to continue to be competitive. Participants attending this summit can take away lessons and get motivated to emulate the award winners in their own companies.

This figure shows a TEEP of 41%, which is typical of many companies who start measuring OEE

Optimising Metal Working Process

Combination tooling: This is a favourite approach of many companies in large volume production. Combination tools certainly lead to cycle time reduction on VMCs and HMCs. There are a few problems that arise. Cutting speed is compromised to increase the tool life of that tool which has the shortest tool life. All tools do not wear the same amount at the same time. This is an issue especially in solid carbide tools while resharpening. Chips from one tool can clog into an adjoining tool. Since cutting parameters cannot be optimized for all the tools, chip breaking can be an issue. Spindle Power increases and the same needs to be checked. Roughing with a combination tool is acceptable but not finishing because the finish is affected when another cutting edge leaves or enters a cut.

Introducing LCA: LCA or Low Cost Automation aids are often used to improve productivity especially where assembly operations are concerned. Certainly this boosts productivity and motivates the workmen. Another advantage is that this knowhow is retained in-house. To design LCAs needs investment in training of personnel. It needs a strong 5S, Kaizen and enabling culture in the organization.

Optimising the cutting tool and parameters: Selection of the correct cutting tool and optimizing the cutting parameters is crucial to reducing cycle time and increasing tool life. Companies have invested in higher cost tooling and using higher cutting parameters and reduced the per piece cost because of higher utilization of the power and capacity of the machine and reducing the cycle time. Monitoring the spindle load and ensuring that it is optimally utilized is an approach used by many companies. This approach needs strong data collection to validate the results and periodic monitoring.

Using CAM programming: Companies have also studied the tool path and reduced the air cutting travel, thereby the spindle is cutting metal rater than cutting air. Sometimes due to lack of discipline and special causes that take place manual changes are made in the program and optimized cycle times are diluted.

Improved Fixtures and use of Accessories: Some companies have taken the approach of redesigning fixtures to accommodate family of parts. Others have modified fixtures to reduce setups. Some others have added 4^th Axis or additional axis on their machine to reduce multiple clamping and setups.

Deburring: Deburring is a troublesome process in most companies. Several approaches have been used including developing special tools to deburr on the CNC machine itself, to using different media to deburr. This needs extensive trials to validate the process including customer acceptance.

Use of DOE and ANOVA: For optimizing cutting parameters Companies have used ANOVA and DOE extensively with encouraging results. This however needs good in-house understanding of the process variables and the technique.

Better Asset Utilization

Utilisation of Generator Sets: Due to power outages in our country Companies have had to use in-house generated power. In most cases where the machine shop is large, several generators feed into a grid. An IT based solution has helped companies to optimally use generators based on variable load.

Reducing power consumption: Most machines have several motors for auxiliary functions, eg. coolant pump, chip conveyor, hydraulic power pack, etc. An innovative approach was to replace these motors by mechanical linkage driven by the main motor and thereby reduce power consumption. This approach may not work in all applications but companies have used one motor between two machines, eg. one coolant pump between two machines. The only problem is if the pump fails both machines would stop at the same time.

Refurbishing and upgradation of old machines: Reconditioning of old machines is an old story. In some cases especially in very large sized old machines, which are mechanically very robust Companies have not only refurbished but considerably upgraded them with latest features. While this works where the company is competent to carry out the work and the cost of a new machine is extremely high, it may not be advisable in many cases as technology has evolved and this would just lead to a compromise solution.

Design standardization: This is a route several companies have taken to improve the productivity in their design department where resources are generally a constraint. This approach needs a disciplined and a system based culture in the organisation.

Nesting: Improved nesting in powder coating, painting and heat treatment processes has led to significant increase in asset utilization and therefore productivity. This needs a deep study to understand the effect of higher nesting and validation of results in the longer term.

Layout and flow improvement in machine shop and assembly: Several companies have used this approach to improve productivity. Line balancing is a challenge but can be overcome.

Minor and idling losses: Several companies have looked at minor and idling losses in their machine shop and assembly areas. Small reductions and elimination of these losses have resulted in a cumulative reduction which is quite significant.

Productivity through quality

Process variable optimization: Heat treatment distortions can be reduced by optimizing various parameters such as temperature, soaking time, quenching time etc. This is an approach some companies have adopted to reduce rejections on thin walled parts.

Poka Yoke: Poka Yoke is a common approach adopted by most companies for eliminating rejections. Innovative means are used with low cost sensors, reed switches, motion counters to eliminate rejections.

Dimension changes in drawings: Assembly rework can be considerably reduced by revising the nominal dimensions of mating parts in an assembly after stack up tolerance analysis. The machining process to maintain the nominal dimension was critically assessed. Simply increasing the tolerance is not the correct solution.

Part cleanliness: Component cleanliness is a major issue in several industries. Companies have approached this challenge innovatively by studying chip formation, chip breaker design, chip evacuation, process changes, etc. The approach is to ensure that machining chips do not remain in the part in the first place.

Repeatability of measuring equipment: Often one takes for granted the repeatability of a measuring instrument and looks for reasons elsewhere. Critically and periodically assessing repeatability of measuring instruments has helped some companies to improve quality and hence productivity.

Improper part handling: Companies have found that improved part handling leads to lower rework and rejections. Though this is not new, part design is tweaked from the point of view of ease of handling during the process.

Manufacturing system redesign

Single piece flow: Several companies have adopted single piece flow against batch production to boost productivity. While this certainly improves productivity and drastically reduces in-process inventory, line balancing and reliability of each equipment is very important. Besides reliability of each equipment, the MTTR for each equipment must be very low otherwise there is complete loss of production. There remains a challenge to convert batch processes like heat treatment, washing, etc to a single piece flow.

SPMs to CNC: In moving from SPMs to CNC, companies have overcome the challenge of frequent setup change over using SMED and thereby improved productivity. This needs a disciplined and planned infrastructure to be sustained. The need to do this arose from fluctuations in customer demand and frequent introduction to new products.

Holistic view of the process: While redesigning the manufacturing system, companies have taken a fresh look at the system. Companies have introduced single piece flow, cellular manufacturing, Kanban, SMED, LCAs and innumerable Kaizens. The resulting benefits are huge. Value stream mapping is a commonly used tool to uncover waste in the system. Factory layouts have completely changed as a result. To do this, the management must be forward looking, bold in taking decisions, and take counter measures in advance to foresee disruptions, which to some extent are inevitable at least in the initial phase

The National Productivity Summit 2015 at Gurgaon on 20 -21^st Nov, showcases through its case studies and keynote addresses how teams have significantly improved productivity at their workplace. Various tools have been effectively used by these teams to discover and analyse the hidden losses in their process and find innovative solutions to challenges thrown at them by their customers. This “out of the box” thinking is very important for these companies to continue to be competitive. Participants attending this summit can take away lessons and get motivated to emulate the award winners in their own companies.