Increase Efficiency using Six Sigma Technology - Essay Example

Six Sigma is a quality methodology that increases profits by reducing costs associated with quality issues and warranty problems. It focuses on reduction in variations of process and product quality characteristics which are critical to the customer. At Company EX., one warranty claim for defective paint or a bad bearing of products can be tens of thousands of dollars; and that does not include potential lost business due to bad company reputation. Statement of the Problem Company EX. has implemented lean manufacturing in February 2008. This has resulted in waste reduction in the company’s operations.

However, the company would like to improve customer satisfaction further by reducing in variations of process and product quality characteristics which are critical to the customer Purpose of the Study The purpose of this study is to improve customer satisfaction by using the six sigma quality improvement methodology to compliment the implemented lean methods to the customer Assumptions of the Study This study will focus on the paint system at Company EX.. Definition of Terms Six sigma – a business process by which waste or defects are removed by focusing on process or outputs important to the customer.

DYNAMIC – Define, Measure, Analyze, Improve and Control 2 Value stream mapping – a technique used to identify material and information flow for a product or service to the customer. Lean manufacturing – business process by which waste is eliminated. ACT (Critical to quality) – needs that the customer has in deeming the product quality KEPI – Key process input variables KAPOK – Key process output variables Standard Deviation – Shows how much variation exists from the mean ASTM – American Society of Testing and Materials is an international organization that develops and publishes testing standards Limitations of the Study

This study will use the DYNAMIC process; due to the scope of the project, only define, measure, and analyze phases will be used. Improve and control phases will be up to Company EX.. Occasionally, special coatings are sent to other companies for paint; these products will be omitted from this study because we do not have control over their processes. In addition, customer is also aware that there is a longer lead time on the product if special paint is chosen. Methodology This study will focus on the paint process.

The processes will be mapped and critical to quality processes will be identified for improvement. Aspects such as first pass yield, scrap costs and process wait time will also be considered and specific periods of time will be chosen to collect data for further analysis. 3 Chapter II: Literature Review Companies Tums to improving quality to increase profits and improve company perception. Warranty and scrap can be easily calculated in most production operations. However, the cost of quality can be difficult to calculate due to external failure costs.

Customers tend to shy away from companies with bad reputations due to poor quality records. The proceeding will show Six Sigma quality methodologies re used to improve process outputs yielding reduced warranty work and improved customer satisfaction. Carl Frederick Gauss (1777-1855) introduced the concept of the normal curve which is the beginning of the mathematics behind Six Sigma. Six Sigma Walter Shareware demonstrated that three sigma from the mean is the point where a process requires correction (Broaching 2005).

Walter Shareware also developed the Shareware Learning and Improvement cycles which combines creative management thinking with statistical analysis. The Shareware cycle includes a continuous process of Plan, Do, Study, and Act or PADS. Other measurement standards (Process capability ratio, Zero Defects, etc. ) were later introduced, but credit for coining the term “Six Sigma” is given to Bill Smith a Motorola engineer (Summers 2006). Six Sigma is federally licensed by Motorola (Propel 2006).

In the early and mid-ass’s, Motorola engineers decided that the traditional quality levels for measuring defects in thousands of opportunities didn’t provide enough information. A new standard of measuring the defects per million opportunities was developed and thus created the methodology and needed cultural change associated with it. The Motorola research provided powerful bottom line results in their organization; greater than $16 Billion in savings was documented as a result of the efforts. 4 Industries around the world have adopted Six Sigma as a way of doing business.

This is a direct result of many of America’s leaders openly praising the benefits of Six Sigma such as Larry Bossily of Allied Signal (now Honeywell), and Jack Welch of General Electric Company. Honeywell International has been utilizing Six Sigma from since the early ass’s. The Six Sigma program was center around manufacturing and operational productivity gains. The Six Sigma productivity gains were so successful that Honeywell was the benchmark for productivity gains. Honeywell Six Sigma model had been modified and expanded to be used for the market place and business. The new Honeywell Six Sigma model is called the Six Sigma Plus.

The Six Sigma Plus model concentrates on sales, marketing, product development, business, and strategy development processes. The emanation of Six Sigma Plus uses the traditional DYNAMIC mechanism to compose a road map for productivity gains (Broaching 2005). An interesting aspect of Six Sigma is the resistance from individuals. Six Sigma is not used by Motorola today, but on the contrary, Motorola may not be in business today without Six Sigma. Motorola started Six Sigma, others have improved it. General Electric actually boasted billions from using Six Sigma (Broaching 2005).

Customer focus and key business initiatives are two focus features that distinguish Six Sigma from quality models such as Quality Circles and Total Quality Management (Broaching 2005). A key principle in Six Sigma is finding the root cause of problems requires a look at processes further upstream to find the root cause. Dealing with the robber is far less effective than dealing with the inputs and the outputs of the root cause of the problem (Broaching 2005). One of the formidable pioneers in Six Sigma, Forrest W. Broglie Ill (Broglie 2003) talks about SO/lee which is Smarter Six Sigma Solutions with Integrated Enterprise Excellence.

This SO/lee approach goes beyond traditional Six Sigma and integrates enterprise measures and improvement methodologies such as Lean and theory of constraints. SO/lee serves an example of how Six Sigma is evolving and improving from its inception by Motorola in the ass’s. The concept of input! Output can be demonstrated in everyday devices such as a light switch. Flipping the switch turns the light on which is an archetype of an output also called a KAPOK (Key Process Output Variable), ACT (Critical To Quality), or the YK’s in the process (Broglie 2003).

For example, when a light switch is switched on the output is light; looking at the light switch from a Six Sigma standpoint, the KAPOK is switching the light on which is made up of KEPI s (Key Process Input Variables) like the striker plate making contact with the power. The power and striker plate are KEPI s that effects the downstream output y which trying to understand the root cause of the output. Along with finding the root cause of problems is a development of measures based off the outputs or the customer wants; these Acts will be talked about later in the chapter under the define portion of the DYNAMIC process.

The DYNAMIC is a cornerstone process that Six Sigma uses in providing the Acts to the customer; the DYNAMIC process is also talked about in the later part of this chapter. More detail quality measures and analysis techniques will further explain the concepts and idea around Six Sigma and ultimately providing the customer their needs or Acts. It is important to create a management framework to support the implementation of Sigma. This framework guides organizational decisions regardless of the scope or action and it is step one for implementation and assist management to believe in the successes and benefits of Six Sigma (Propel 2006).

The management framework should include operational concepts, values, and norms for day to day operations. It also includes the vision for the organization, how 6 this is to be realized and management style needed for successful Six Sigma implementation (Propel 2006). Numerous leading companies such as Home Depot and MM have adopted Six Sigma or advantages which include increased profits and customer satisfaction (Precook 2006). The six sigma is a model that sets a customer focused performance goal for the entire company. Lean manufacturing was predominantly derived from Toyota Production System.

Lean manufacturing simply attempts to reduce waste. Lean focuses on reducing waste which translates to a more productive system. Six Sigma maps the process and reduces defects (Woman and others 1990). Six Sigma and lean manufacturing complement each other. Six Sigma is focused on variability reduction while lean focuses on reduction in waste. Define, measure, analyze, improve and control (DYNAMIC) is the process to follow when doing a Six Sigma project (Broglie 2003, Steven 2009). The Six Sigma DYNAMIC process is not very different from any other the problem and not Just provide a temporary fix.

The proceeding sections will explain what DYNAMIC is and how they are used in a Six Sigma project. In the define phase the problem is defined. Then the processes that can create issues for the customer if they are not correct such as paint or a loose bolt and critical to quality (ACT) for the customer are identified. The product flow is then mapped and the steps radical to the customer are identified (Cakes 2005). A process flow map is simple chart that uses objects and arrows to show an overview of key process (Broaching 2005).

This map shows where potential problems are this enables the team to focus on the root cause of those potential problems. The process map also allows the Six Sigma team to find the key process input variables (KEPI) and the key process output variables (KAPOK). KEPI are those input steps, 7 processes or actions that provide the KAPOK. The KAPOK are those outputs that are valued by the customer (Broglie 2003 In the measure phase, the identified Acts are measured. Measuring or tracking is the key point in this section. The DYNAMIC process measures what is important to the customer (Propel 2006).

The define phase segregated the KEPI and KAPOK from the process map, so measuring is based on these. KEPI and KAPOK were selected because they were most critical to the customer. The data gathered is organized for analysis. Analyze phase involves statistical analysis of the data collected in measure phase. The data should be graphed, charted and descriptive statistics obtained to draw conclusions (Broglie 2003). The statistics of interest here are the mean and standard deviation. The mean is the average in a population. This is calculated by simply adding the data set up and dividing by the number in that particular data set.

The mean shows where most of the data points are lying (Evolved and Rotor 1993). Any process goal is for the mean of the process ACT to meet nominal value of the quality characteristics of interest to the customer. The standard deviation is a well understood mathematical function that gives another perspective of the data set. Mathematically, the standard deviation is the square root of the variance which is a assure of variability or dispersion of a data set. Simply put, standard deviation shows how much variation exists from the population mean or average.

Ideally, minimal process variation would exist; graphically data points would lie close to the mean showing a small standard deviation. An important piece of standard deviation is the normal curve also known as a Gaussian distribution. The normal curve describes data that clusters about the mean which is associated to the probability density function. Graphically, the normal curve looks like a bell shaped cure peaking around the mean. A large standard deviation shows that the 8 data is spread out with respect to the mean, while a smaller standard deviation shows the data’ points are closer to the mean (Clark 1992).

Sigma (cry) is commonly methodology, six standard deviations from the mean is the goal which equates to a large percentage of collected data lying plus or minus the mean. Another way to think of this is the upper and lower control limits are within six standard deviations of the mean which equates to 95% of the good parts lying within those limits and one standard deviation plus or minus equals 68. 2% of the data. Data close to the mean signifies that there is minimal process deviation or processes that are out of control. Mathematically, six cry equates to 3. Defects per million (Broglie 2003). Fifteen sigma, for example, signifies a large variability in the data which is not advantageous for tight process control. The upper and lower control limits are used to see how close the data tracks to the statistical mean. The upper and lower control limits are calculated and are mathematically +1- 3 standard deviations about the mean. Control limits that are very close to the mean are good because 99. 73% of the data is then lose to the mean, this equates to good process control assuming the mean is at a desirable level.