Six Sigma And Total Quality Management

Published Date: 02 Nov 2017

Deming’s concept

Deming (1986) said that it is the responsibility of the leader to lead the process of changes and improvement and without top leadership commitment; the goal of bringing changes and continuous improvement cannot come true. Deming gave his 14 points which are the basic principles of TQM implementation.[1]

Juran’s concept.

According to juran (1993) the main target to TQM is customer & employee satisfaction, more profit and low cost. Juran furnished his idea as that main reason of quality problems is management not the workers, and to achieve the quality goals all the functions of organization must work in a synchronized way.

Internal failure cost.

External failure cost

Appraisal cost

Prevention cost[2]

Crosby’s concept.

Crosby focused more on employee training and education as well as reduction of cost of quality. He gave the idea of doing things right first time and zero defects. Crosby that the problems are created by two reasons, lack of knowledge and lack of concentration and commitment towards work.[1]

2.3 Quality Control

As per USA standards quality control refers all types of planning activities implemented within the quality system, which are always expected to provide adequate confidence that an organization will fulfill requirements for quality. QC use techniques and activities to achieve sustain and improve quality of products or service. It integrates these related techniques and activities. Quality control is the method of monitoring the process to attain the exact specifications for the product which is required and demanded by the customer. QC is the process of designing the product before starting the production to confirm the Design of the products or service to meet specs. It’s a Method of inspecting the process to have its production or installation to meet full intent of specs. Review usage to provide information for revision of specs. if needed the aim should be towards quality improvement[3]

2.4 Quality Assurance

American Quality control society views on assurance of quality as the Quality planning tool with systematic activities for a product or service will be fulfilled by the proper assurance method. From the quality control definition, we can say that quality assurance procedures and activities done before the product or service is manufactured and delivered to the customers as a good quality product. This is a proactive approach. By which we can eliminate the complete dissatisfaction of customers and increase the loyalty and image of the concern as they are the best in market to supply quality products to the customer satisfaction. All those planned actions necessary to provide product or service will satisfy given requirements for quality which needs systems and procedures to ensure consistency in methods for producing products. [3]

4.3 Procurement

The Quality Management provides data for processing the quotations from the supplier and purchase orders. For example, if there is a small problem in quality of product we are not allowed to place purchase orders for a specific vendor who has to sign the contract which compiles the delivery terms and the quality standard agreements with the quotation. Since delivery terms are indicated for a purchase vendor, the long text is printed out which is commonly called as purchase order. When the goods are ordered, you can request a certificate from the vendor for the respective material, if certificate is not supplied the goods are not allowed to move further without the inspection for product lot. Quality Certificate is must when the purchase decision is made. [7]

Production

Quality is the process for manufacturing quality products meets the required quality at all times. The aim of Quality is to produce the right product at the first time, without any rework. Nowadays all Organizations have a individual department to assure the quality of their products or they may have consultants. Quality is very crucial for the manufacturing industry. Since no manufacturing industry are ready to spend time and money on rework. Every activity in the industry costs money they do not pay for rework. Customers expect more valuable additions for the product when compare to other products in the market at same price or lower price, they will move to that company. Hence to assure good quality to customers, quality plays a significant role in manufacturing process. [6]

Deming’s prize is the most famous quality award in the world and was started in 1951.After II world war, Japanese industries were totally demolished and they started their industries again and in order to rebuild their industries on firm bases they invited famous American quality guru Dr. Deming to Japan, and his work there helped Japanese industries to compete in world market in a very short time. In order to commemorate his work the Japanese union of scientist and engineers started a quality award for those industries who out classed other in the field of quality management. There are numbers of award categories like

Deming’s prize for individuals

Deming’s prize for large organizations

Deming’s prize for small organizations

Deming’s prize for company divisions

Deming’s prize for non Japanese oraganizations.

In the very beginning this prize was only for the application of statistical process control methods like DOE, SQC, value stream mapping ,FMEA and so on but with the passage of time it started covering all total quality management field awarded by Union of Japanese Scientist and Engineers. [3]

9. TAGUCHI METHOD AND STRATEGY:

The goal of the Taguchi method is to reduce costs to the manufacturer and to society from variability in manufacturing processes..

l\left(y\right)=k_{c}\left(y-\tau\right)^2

The constant, kc, in the loss function can be determined by considering the specification limits or the acceptable interval, delta.

k_{c}=\frac{C}{\Delta^2}

The difficulty in determining kc is that τ and C are sometimes difficult to define.

If the goal is for the performance characteristic value to be minimized,

l\left(y\right)=k_{c}y^2\qquad Where\qquad\tau=0

If the goal is for the performance characteristic value to maximized,

l\left(y\right)=\frac{k_{c}}{y^2}

By computing these loss functions, the overall loss to society can also be calculated. [8]

10.1 Randomization

Randomization – a statistical tool used to minimize potential uncontrollable biases in the experiment by randomly assigning material, people, order that experimental trials are conducted, or any other factor not under the control of the experimenter. Results in the effects of the extraneous factors that may be present in order to minimize the risk of these factors affecting the experimental results. The sequence of conducting the experiments should be random.

10.2 Replication

Replication – repetition of a basic experiment without changing any factor settings, allows the experimenter to estimate the experimental error (noise) in the system used to determine whether observed differences in the data are "real" or "just noise", allows the experimenter to obtain more statistical power (ability to identify small effects) The number of times each experiment is repeated. The main objective is to estimate the error or inherent variation in the process.

11.1 Planning the Experiments:

Everyone involved in the experiment should have a clear idea in advance of exactly what is to be studied, the objectives of the experiment, the questions one hopes to answer and the results anticipated

Select a response/dependent variable (variables) that will provide information about the problem under study and the proposed measurement method for this response variable, including an understanding of the measurement system variability

Select the independent variables/factors (quantitative or qualitative) to be investigated in the experiment, the number of levels for each factor, and the levels of each factor chosen either specifically (fixed effects model) or randomly (random effects model).

Choose an appropriate experimental design (relatively simple design and analysis methods are almost always best) that will allow your experimental questions to be answered once the data is collected and analyzed, keeping in mind tradeoffs between statistical power and economic efficiency. At this point in time it is generally useful to simulate the study by generating and analyzing artificial data to insure that experimental questions can be answered as a result of conducting your experiment.

12.2. How Does DOE Fit in the SIX SIGMA Tool Box?

DOEs are performed in the "Analyze" & "Improve" phases of the "DMAIC" in that phase breakthrough Strategy DOEs determine the impact that variables have on a product or process characteristic which can monitored by Process Maps are by doing FMEAs to identify the inputs (x) to be investigated and or validated by Process Mapping & FMEAs to find identify what outputs (y) need to be measured. MSEs are performed on all important measurement systems before the DOE. [20]

Figure : DMAIC CYCLE. [4]

12.2.1 Six Sigma and Total Quality Management:

Six-Sigma is a combination of business philosophies to gain more profit and to fulfill customer requirements. Six-Sigma is acting as a strategic and cultural change in a company which implements new vision, develop the competencies, build activated teams and great infrastructure for the company to keep on sustainable improvement. The Six Sigma activities by applying proper tools and techniques such as TRIZ or QFD will make use of resources more effective and efficient. It increases customer satisfaction by eliminating causes of dissatisfaction, improving performance and introducing unexpected features and finally enhances the value of the product. This method can be very effective for a company but it is also connected with a lot of effort to implement the basic principles and to convince every employee to take part at this strategy. Six sigma has two main concepts. The first is to reduce the defects to 3.4 defects per Million opportunities as a statistical approach. The other one is a business perspective, which focuses on increasing the profit and customer satisfaction. Total quality management established well before Six sigma methodology and six sigma carries some of the TQM theories. TQM focuses more on improving thing by collaborative and cultural approaches while Six-Sigma is more of a data drive system. Total Quality Management is a comprehensive quality management system to achieve the market leadership for a company. This approach extends on all different areas of the organization as Six Sigma does. However, in contrast to Six Sigma, TQM is included in the daily work of the employees. The projects are not selected systematically and it is more an improvement step by step then as a radical change, as Six Sigma does. Also the main focus of total quality management system customer’s satisfaction & meeting customer demands and if there is no customer there is no company but opposite to this in six sigma the main focus is to generate large profits and meeting customer demand is seen as one way to generate more profit.

The theory of Six Sigma is strongly connected to different approaches of quality management systems. In their implementation it uses different tools of the given theories, but is still an own philosophy.

12.2.2 Implementation of TQM by implementing DOE.

Total quality management as a measure or tool for improving the organizational performance has captured the attention of many authors and researchers. It is agreed by many researchers that long term success of total quality management in an organization relies on its effective implementation. The process and tools like DOE through which total quality management is implemented in the organization plays major role for success. Thus, the success of total quality management owes a great deal to the effective implementation. For the effective implementation of the total quality management, organizational people should be very careful in selecting the Quality tools for correcting the problems and solving the errors without any kind of wastes.

Implementation of total quality management in the organizations is very important because of many reasons. Central to theses is that effective implementation of total quality management must have positive influence on the behaviors, attitudes and values of employees. Initial phase of implementation by selecting proper tools and techniques for the company’s total quality management has long lasting impact on its success.

14. ADVANTAGES AND DISADVANTAGES OF DOE:

Taguchi method emphasizes a mean performance characteristic value close to the target value rather than specification limits. Additionally, DOE is mainly used to quickly narrow down the scope of a project or to identify problems in a manufacturing process from existing datas. For example, a process with 8 variables, each with 3 states, would require 6561 experiments to test all variables. By Taguchi's orthogonal arrays, only 18 experiments are necessary, or less than .3% of the original number of experiments. [9, 15]

14.1. Disadvantages of DOE:

Taguchi method gives only relative and do not exactly indicate what parameter has the highest effect on the performance characteristic value. Another limitation is that the Taguchi methods are offline, Furthermore, since Taguchi methods deal with designing quality in rather than correcting for poor quality, they are applied most effectively at early stages of process development. This most often lead to have a considerable artificiality for practice. [9,13,15,19]

Step 1: Design of experiments and the Taguchi approach:

A quick understanding of the Taguchi DOE method is very much essential before starting the subject

Step 2: Definition and measurement of improvement:

Consistent performance produces reduced variations. From this step, you can learn how population performances are measured and compared.

Step 3: Common experiments and analyses methods:

A more effective method to study and for effective practice is by setting up experiments with help of DOE technique.

Step 4: Designing experiments using orthogonal arrays:

A number of standard orthogonal arrays are constructed only for facilitating the designs of experiments and to learn about the different orthogonal arrays and understanding how easy it is to design experiments.

Step 5: Designing experiments with two-level factors:

Experiments that involve studies of factors with two levels are simple, common and created specifically for two-level factors. 

Step 6: Designing experiments with three-level and four-level factors:

Although many larger two-level orthogonal arrays can be modified to accommodate three-level and four-level factors, a set of standard arrays are available for this purpose.

Step 7: Analysis of variance (ANOVA):

This step teaches you how to analysis of variance terms are calculated to build your confidence in interpreting the experimental results.

Step 8: Designing experiments to study interactions between factors:

In this step we can get an clear idea of DOE tool application methods to solve most production problems whose solutions lie in finding the exact cause and controllable factors, instead of spending time only on some special causes.

Step 9: Experiments with mixed-level factors:

In this step our goal will be to learn the procedure to upgrade and downgrade the number of levels in creating a new column.

Step 10: Combination designs:

This step will familiarize you with the necessary assumptions to lay out experiments using combination design.

Step 11: Robust design strategy:

This Robot design strategy is promoted by Taguchi to reduce variability without eliminating variation causes.

Step 12: Analysis using signal-to-noise (S/N) ratios:

This step will give you a brief idea for calculating MSD and its quality characteristics.

Step 13: Results analysis using multiple evaluation criteria:

This step is to spend your valuable and quant able time in learning the principles involved in formulation for analysis of multiple objectives.

Step 14: Quantification of variation reduction and performance improvement:

This step teaches how to estimate the expected savings from the experimental results.

Step 15: Effective experiment planning:

The nature of discussions in the planning session to vary from project to project which can be facilitated by one who is expert in this technique.

Step 16: Review of example case studies:

Way to build more confidence and extend your application expertise is by familiarizing case studies with complete experiment design. [7,21,22].

19.1 Traditional Brainstorming

The brainstorming in old days is practiced to have or assemble a group of people to sit in a room and shout out ideas as they occur to them. So that people are free to shout out any ideas at all without feeling uncomfortable. People should build on the ideas called out by other participants. The purpose of this action is to gain ideas from various point of views for later analysis. Out of the many ideas suggested there will be some of great value. Because of the free-thinking environment, the session will help promote radical new ideas which break free from normal ways of thinking. {Sule 2008 #9}

19.2 Advanced Brainstorming

As the extension of the traditional brainstorming scenario process easier and more effective. Advanced brainstorming builds on the current methods of brainstorming to produce more original ideas in a more efficient way. Most of the problems associated with traditional brainstorming disappear as a more effective process is used. By reading for more details of how you can do advanced brainstorming for great profit to you and your organization.{Pande 2001 #15}

19.3 Brainstorming Steps:

Gather the participants from as wide a range of disciplines with as broad a range of experience as possible.

Write down a brief description of the problem - the leader should take control of the session.

Use the description to get everyone's mind clear of what the problem is and post it where it can be seen.

Encourage an enthusiastic, uncritical attitude among brainstormers and encourage participation by all members of the team.

Do NOT interpret the idea; however you may rework the wording for clarity's sake.

Do NOT evaluate ideas until the session moves to the evaluation phase.

Do NOT censor any solution, no matter how silly it sounds. The silly ones will often lead to creative ones - the idea is to open up as many possibilities as possible,

Once all the solutions have been written down, evaluate the list to determine the best action to correct the problem.

The success of this process depends upon the member's expertise and communication skill. Also, each response requires adequate time for reflection and analysis. The major merits of this process are. {Pande 2001 #15}

Elimination of interpersonal problems.

Efficient use of expert's time.

Diversity of ideals.

Accuracy of solutions and predictions.

The figure below gives my brainstroming methodology suggested to be followed in mechanical industry to improve the yield or to the correct the problem in experimental manner. [6]