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What is DMAIC - Six Sigma

by Joz Joneda on February 25, 2011

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 really

Pareto Chart

by Joz Joneda on February 25, 2011

Pareto 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 behind

TPM

 

(Total Productive Maintenance) as a waste elimination tool

Today we discuss about Total productive maintenance(TPM) as a waste elimination tool.

TPM defined as TPM (Total Productive Maintenance) is a maintenance philosophy designed to integrate equipment maintenance into the manufacturing process.

The goal of any TPM program is to eliminate losses tied to equipment maintenance or, in other words, keep equipment

Six Sigma Keys to Quick Lean Maintenance Reliability

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


Optimizing Total Cost of Ownership

 

By Jim Humphries and Brad McCaleb -- 7/1/2004

 

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.

  • Physical life is the expected age of a component when the cost of a repair is, or will be, greater than the cost of replacement
  • Economic life is the age of a component when the present value of future life-cycle costs (i.e., maintenance, operations, energy, and opportunity costs) is expected to exceed the present value of life-cycle costs, including purchase cost, for a new component of the same design. Economic life never exceeds physical life
  • Technical life is the age of a component when it is technically obsolete. A component is technically obsolete when required parts or repair skills are no longer readily available. Similarly, a component is technically obsolete when a newer version of the component or newer technology offers significantly lower operating or life-cycle costs than the component in question. Since a component may become technically obsolete either before or after the initial wear-out period, technical life can be either greater or less than physical and economic life.

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:

  • Engineering
  • Purchase costs, including freight, taxes, costs for purchasing, receiving, inspection, etc. and costs associated with expediting late deliveries and/or handling defective parts
  • Installation
  • Startup, debugging
  • Operations and maintenance training
  • Spare parts, tools, and maintenance materials
  • Operator labor
  • Maintenance labor
  • Fuel and energy
  • Lost earnings from unavailability (i.e., margin contribution or contribution to overhead and profit from incremental changes in product volume rather than net margins discounted by fixed costs)
  • External renewal, rebuild
  • Decommissioning and removal
  • Resale or disposal after removal.

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:

  • Selection of alternative components (Except when the differences in options are limited to differences in price or lead times, all component purchase decisions should be based on some form of TCO analysis)
  • Selection of alternative process or system designs (e.g., with and without redundant components)
  • Evaluation of alternative maintenance strategies (Focus is usually on renewal or rebuild frequencies, but can also include selection/scheduling of condition-based maintenance, spare parts, etc.)
  • Fleet renewal frequencies
  • Repair versus replace decisions
  • End-of-useful-life decisions (e.g. when to retire an operating plant)
  • Selection of optional component or service suppliers.

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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