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What is DMAIC?
DMAIC is the structured Six Sigma approach for process improvement: Define, Measure, Analyze, Improve, Control. Six Sigma Black Belts are well versed in the DMAIC approach, and are typically certified within their business or through a dedicated training organization.
The DMAIC process can be applied to any situation where a process, be it physical (i.e. manufacturing) or transactional, is producing measurable results. Examples of measurable results are endless, and just about anything worth measuring can be measured, if the management team reallyPareto Chart
The Pareto Principle (also known as the 80/20 rule) states that in many situations, a small number factors will influence a given outcome the most, even when there are many more factors in the equation. For example, a student’s likelihood of getting into college will be (mostly) determined by two things: high school grades and standardized testing scores. Books have been written about all the factors that affect college acceptance decisions, but the reality is that excellent grades and competitive testing scores make up the majority of the equation for most schools.
The Pareto Principle is at work everywhere, and the real goal of any Six Sigma project is to find the top two or three factors that make up the true Pareto chart for a given problem, and then control those factors to achieve breakthrough performance. It’s that simple. But finding the true Pareto chart behindTPM
(Total Productive Maintenance) as a waste elimination tool
Today we discuss about Total productive maintenance(TPM) as a waste elimination tool.Focus on equipment hardening (stress elimination) in lean environments to maximize mean time between failures, uptime, reliability and profits.
by Howard Cooper
The maintenance problem
Too many times, in lean manufacturing and other lean environments, 10- to 40-year-old equipment is re-deployed, moved and organized into lean cells without adequate concern or attention to maintenance reliability. In a lean cell, unscheduled equipment downtime usually costs 10 to 20 times what the same equipment downtime costs in old traditional batch processing or functional departments. For example, before “lean” we quoted CNC machine tool downtime at $250–$750 per hour for a single 3- to 5-axis CNC machine or robot. Today, automakers with well-configured lean manufacturing plants quote machine tool or robot downtime costs at $2,500 to $5,000 per hour. That is, until a painting robot misses doing its 7th or 8th car. Then the factory is backed up and downtime cost jumps to $3,350 per minute ($201,000 per hour).
As a maintenance engineer for John Deere Co. in the 1970s, I was highly motivated by downtime figures of $250–$750 per hour. By avoiding 4-6 hours of downtime, I had saved the company my month’s salary. I was motivated to find ways to avoid, reduce or eliminate downtime, wherever I could. How much more motivating is lean maintenance reliability today?
Discoveering a solution
The answer to increasing reliability and uptime of computers, telecom equipment, machine tools, automation controls, hydraulic systems, electronics, etc., used in lean manufacturing and other lean environments can be derived from Six Sigma’s Y = f(x) and DMAIC. That is if you don’t go down the wrong and apparent path, as explained below. Back in the ‘70s we didn’t have Six Sigma, so we started our analysis by gathering “cause,” “effect” and “result” information on each maintenance downtime situation. For example:
· Cause: Bad CAU2 circuit board
· Effect: X–Y axis cutting egg shapes rather than circles
· Result: Scrap parts and downtime
Log books were placed at each machine with this format, and the maintenance situation was detailed by the electrician or mechanic as soon as the machine was repaired and the cause was known and corrected.
Soon our analysis database looked something like the following table:
| Cause | Effect | Result |
| CAU2 board | Egg-shaped cuts | Scrap, downtime |
| Bad memory board | Part ID growing | Rework, downtime |
| Axis drive board | Axis oscillation | Scrap, downtime |
| Spindle CMD board | RPM swings | Rework, downtime |
| Servo valve | Y run to limit | Downtime |
| Bad solenoid | No coolant | Downtime |
| Hydraulic pump | No chuck gripping | Scrap, downtime |
| Hydraulic 3W valve | Turret unclamping | Broken tool holder |
| SCR failed | Z-axis runaway | Downtime |
| CMD board | No X movement | Downtime |
| FE-2A board | Only rapid travel | Broken tool, scrap, downtime |
| Z-PQM drive | Axis not stopping | Scrap, downtime |
| Bad limit switch | X-axis crash | Rework, downtime |
| Bad encoder | Positioning errors |
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| By Jim Humphries and Brad McCaleb -- 7/1/2004
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| When total cost of ownership (TCO) is applied broadly, the tools and concepts enable users to make a measurable impact in plant operating costs and margins. Their value comes from refocusing decision-making processes based on price and purchase cost to consider all financial impacts associated with a decision. The positive impact is achieved through two related activities, analysis and control. Life-cycle analysis, or total cost analysis, is about understanding the relationship between purchase costs, operating costs (including operating labor, energy, maintenance, and the opportunity cost of lost production), and residual values versus the age of equipment or components and versus alternative operating and maintenance practices. Total cost control, also called life-cycle management, and value management, is built on life-cycle cost analysis. It involves manipulating the life-cycle cost relationships and variables to minimize the cost or maximize realized value from an asset. The variables include renewal/replacement intervals, servicing costs, failure consequences, asset redundancy, maintenance strategies, energy efficiency, design life service factor, etc. Tools, such as engineering economics, remaining life estimates, statistical analysis, opportunity costing, and electronic spreadsheets are essential to effective life-cycle management. Engineering economics enable us to consider the time value of money when comparing alternatives, while life estimating provides common vocabulary and technical tools for relating physical and financial attributes of a plant component. Opportunity costs expand life-cycle and total cost considerations to include financial losses from component downtime and loss of function. Statistics allow us to consider the variability of expected life-cycle costs estimates, and spreadsheets give us the ability to combine all of the tools to easily model financials for our alternative policies, strategies, and buying decisions. Component life Certainly, the concept of component life is at the heart of life-cycle management and total cost optimization. Actually, component life refers to three different but complementary concepts.
Life-cycle cost analysis A total or life-cycle cost analysis normally evaluates numerous kinds of cash flows and financial impacts over the expected physical, economic, or technical life of a component or facility. They can include:
Optional suppliers for the same part or component functionality can also be evaluated based on the total of these cost elements. Life-cycle value analysis A life-cycle value analysis is quite similar to a cost analysis. In a cost analysis, costs are usually positive numbers, and credits, such as the sale of a used asset upon retirement, are negative numbers. The value analysis reverses signs of the numbers and focuses on revenue generating assets such as production units rather than plant components, which do not create revenue generating products by themselves. In either case, the analyst forecasts costs and credits and searches for ways to reduce cost while increasing credits. In an industrial environment, TCO and life-cycle analysis provide the best approach for making the following kinds of decisions:
Process When applied to these decisions, TCO optimization follows a process. Here are the six steps. 1. Clarify alternatives The key here is to gain a clear understanding of the scope of each alternative and to assure an "apples-to-apples" comparison. For example, it would be inappropriate to compare a plant component to a system of plant components unless the system and the component serve exactly the same function. 2. Establish discount rate To properly compute net present values as the basis for decision making, the time value of money must be represented accurately with the appropriate discount rate. A common mistake is to use the prime interest rate instead of your company's weighted average cost of capital (WACC). If in doubt, consult your chief financial officer. 3. Determine appropriate planning horizon Evaluating alternatives over too long or too short of a planning horizon can also cause errors in net present value (NPV) computation. Generally, you want the planning horizon to be for the time period during which your decision among alternatives should apply. For example, if you are looking at alternative plant designs for a product that will be obsolete in 10 yr, use 10 yr as the planning horizon rather than 20 to 25. Component and fleet renewal decisions are notable exceptions to this rule of thumb. When comparing options of unequal duration (e.g., replacing forklifts every 3 yr versus 5 yr), the planning horizon should be the smallest multiple of all options considered so there is an integral number of cycles for all options (e.g., 3 x 5, or 15 yr for the two forklift options). 4. Build life-cycle cost spreadsheets with cost estimates for alternatives The norm is to create a spreadsheet for each alternative. The spreadsheet is a matrix showing a series of time-period cost estimates on a spreadsheet row for each of the cash flow or financial impact types discussed previously. In the far right of the spreadsheet, a cell computes NPV for the row, and a total NPV cell at the bottom of the spreadsheet computes the sum of NPV figures for each row. Establishing the estimate of life, period maintenance costs, residual values, and the other life-cycle cost components can be a very involved process. However, the analysis rarely needs to be time consuming or expensive. The trick is to expend an appropriate level of effort. For example, if maintenance costs for two alternatives are unknown but believed to be equal, the ultimate decision will not be impacted by the maintenance costs. Spending effort to get a finely tuned and equivalent maintenance cost for the two alternatives will not change the answer and should be avoided. |
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