Book Release with two free gifts : -7 Essentials in Supplier Quality Management

Click on the photo below!!👇

I have decided to start my first book base on my subject matter of expertise in supplier quality management.  Two decades of my experience in systematically managing supplier quality to achieve consistently good quality products is shared in this book.

Company success relies heavily on the quality of material received from the supplier along the supply chain. Many organizations had been struggling with low-quality incoming part from suppliers and pay way above the actual material cost to manage those inferior quality parts.   Imagine an organization have a customer who is ready to buy the product; however, there is no material to transform the product into sales. Almost all supplier delivery problem is associated with the supplier having quality issues which had caused limited supply or inferior quality product. It is nearly impossible to turn defective materials into good quality products.  

Organizations are paying way above the actual material cost due to poor quality as additional cost are incurred in the following areas:-

1.  Defective material inventory cost
2.  Transportation of poor quality material
3.  Storage space to store poor quality material
4.  Hire more workers to screen inferior quality parts
5.  Compensation cost to customer due to late delivery

This book focuses on a systematic approach in 7 essentials of area supplier quality to achieve defect-free product from supplier process. This single system would help to reduce variation in managing different suppliers which also leads to consistent results.  In turn, this will enable an organization to receive consistent good quality part to feed the manufacturing process can convert the product into sales and revenue. There are a total of 16 figures and five tables to summarize a large amount of information which enhance the reading experience of this book.   This book is written by a supplier quality practitioner like me for a supplier quality practitioner. 

Two exclusive gifts are included on

• Guide on how to build a supplier audit checklist and
• Excel format sample checklist.  The reader can directly use the excel checklist to create final quality audit checklist. 

Finally appreciate the support for this book from audiences in this website.  

The book is available through this link:.  You can also click on the photo above to get the link.

https://www.amazon.com/author/evelyntan

Is Quality free - Do not shed a tear until they see the coffin

In my previous article,  we already know the 3 main reasons why quality is not free which are all related to design.

In the past most of the manufacturing processes are very much dependant on human where most of the defect have direct cause are human error, therefore emphasis on “do it right the first time” was focused on the manufacturing process.

If a further root cause analysis is done,  the final cause is actually due to design per the example below. 

A simple example would be doing a 5 why analysis

From the figure above,  it seems that the manufacturing cause is the cause of the component damage when we deep dive the root cause is pointed to the design issue where the component is designed too near to the edge of the board and cause handling damage.

This will increase the cost of manufacturing due to extra control, rework, more inspection and risk of shipping defect to customer. 

We can move towards quality is free by understanding how to prevent or minimize the  4 types of quality cost

Category	Description	Suggested Mitigation  Plan
Appraisal cost	Cost of performing test and inspection on a product to screen out potential defect include inspector.	·       Create testing which replicate customer environment
Internal failure cost	Cost of rework or scrapped product which does not comply to the spec	·       Product design that are error proof
External failure cost	Cost of poor quality at customer site which involve warranty cost, product recall, lost of customer trust	·       Plan in quality per prevention cost plan, then quality is really free
Prevention cost	Cost of preventing a defect through quality planning of design in quality and build in quality	·       Ensure quality function gets involved during the early design stage ·       Benchmark on predecessor product if any to correct the problem ·       Proper FMEA involve all downstream function such as production and customer quality ·       Study how product being used in customer environment and design the part for customer convenience

From the table above,  it is shown that by focusing on preventive cost through proper quality planning would have minimized the appraisal cost and even eliminate failure cost.  Bear in mind quality issues design stage will on 1/1000 of the failure cost at the customer site.

Unfortunately, many organizations choose not to put in effort in quality planning during the design stage and hope the problem will never surface during manufacturing or customer site.   The management mindset does not shed a tear until they see the coffin (不見棺材不落淚 ) had caused them to pay for enormous quality cost especially if failure happens at customer integration. 

Is quality Free - What are the reasons prevent quality from being free?

Many years ago Philip B, Crosby a famous quality guru  wrote a book title "Quality is Free" where he advocates for do it right the first time in the manufacturing process.

To understand the concept of  quality is free, we have to know what are the four categories cost of quality to understand the concept of quality is free per table below:-

Category	Description
Appraisal cost	Cost of performing test and inspection on a product to screen out potential defect include inspector
Internal failure cost	Cost of rework or scrapped product which does not comply to the spec
External failure cost	Cost of poor quality at customer site which involve warranty cost, product recall, lost of customer trust
Prevention cost	Cost of preventing a defect through quality planning of design in quality and build in quality

 

Among all the four components of quality cost,  most organization pay the least attention to the prevention cost.   Zero defect product does not happen by chance as there are many errors which could happen to throughout the product life cycle from birth to grave.  A very prevalent example that very little attention is being given on quality planning during the design phase would be a software product where there are always patches to correct the program.  I am sure all computer user would experience this all the time.  

Often organizations only think that do it right the first time is only applicable during the manufacturing of the product to achieve quality is free.

They are ignorant that product design is the main culprit of the cost of poor quality until it is too late.  

Many organization will never achieve quality is free due to 3 main reasons:-

1.  No attention is given to quality during the early design stage

 

Throughout concept/design till validation phase,  design and marketing team only focus on what is special innovation which will delight customer and customer is willing to pay for it. The normal design approach would be over the wall with little or no collaboration at all with another cross-functional team.  This mean quality planning is neglected.  During the production phase only quality control of inspection/test to filter out the non-conforming product during production which results in the high appraisal, internal failure cost and expensive external failure cost.  It is a ripple effect when there is no investment being made in prevention cost will subsequently result in other 3 quality cost.

 

2.  Unable to surface potential quality problem

The quality issue is always hidden and will only visible under certain circumstances.  Most quality problems happen at customer integration  as

there was a limited user interface study being done on how a customer could use or integrate into the macro environment. 

Another concealed quality problem would be there are not enough sample which represents the population to test out whole range spec. 

DFMEA and PFMEA  which unable to cover all aspect of a potential problem.  A good FMEA requires team member who specializes in quality engineering. 

3.  Short time to market

This is the most classic reason where organization always push for a product launch at the shortest time without taking into account where adequate testing and planning.  

 

Interested to know what does it take to achieve “quality is free”. More in an upcoming article.   

Zero-defect a Myth or a reality – Design For Manufacturability

Design for manufacturability is a must to achieve a zero-defect product where the principle in DFM must be followed. Some of the major DFM principles are:-

1. Design with least part to reduce supplier chain and manufacturing process complexity
2. Design product which is simple to make
3. Consider the availability of raw materials which use design for manufacturability strategy.

The world is haunted by poor design product especially in some traditional industry where the product life cycle is more than 30 years such as industrial equipment and aerospace where those products are designed without design for manufacturability principle. Unfortunately, most of these companies esp. those big multinational companies choose not to acknowledge the poor design of their product. 

The main reason could be political where a large investment had to make and could cause the shareholder to be unhappy with huge investment make to redesign the product.  

To work towards zero defect, there must be rigour and quality awareness throughout the supply chain from the transformation of raw material to piece part, subassembly and final product.   This includes the followings:

1. Product design for manufacturability
2. Product design for simplicity
3. A systematic approach to supplier quality management through 7 essential areas (http://www.7esupplierquality.com/)
4. Control of process input according to what had been discussed in this website
5. Accurate data analysis to understand what contributed to the defect
6. Understand the variation throughout the supply chain

I am sure if all the 6 steps are following through, working towards a zero-defect should become a reality.

Process Input Material - Part purchase from supplier

Material are among the most challenging process input to manage where many companies success are dictated by quality of material they received.  The ultimate objective of every company is to ensure  supplier are able to delivery consistent good quality materials at the best price.  Unfortunately many companies are haunted by poor quality material which had cause them hidden cost which potentially lead lost of business. 

With this in mind,  I had design a systematic approach on how to manage supplier in 7 essential areas.  More  about  7 essential areas in supplier quality management can be found in this course :-

https://bit.ly/Udemy7ESQM

We must put equally important emphasis on process input, material that is purchased from a supplier from another manufacturing entity.   This material will be transformed through a series of process to become a finished good according to customer requirement.

In the modern world,  raw  material  will be transformed into component, sub assembly, final assembly and end item to be delivered to consumer.  All transformation will take place in several entity which form a supply chain.  Therefore almost all manufacturing entity will be heavily rely on supply parts from external supplier.  Incoming parts could dictate a company production and delivery schedule to customer, final part quality and overall manufacturing costs.  

Most organizations would assume supplier are able to supply consistent good parts to feed their production line requirement for raw material.  In most cases this is a myth and the reality is there are many organizations are being haunted poor incoming part quality which causes late delivery to customer and whole the production schedule are being dictated by incoming material.  It is an organization nightmare to live with supplier decommitment of the delivery schedule and poor incoming material quality. 

As material is from external plane  many  companies had either neglected in putting resources to manage purchased part quality or putting resources that had very little knowledge to manage supplier quality.  All pain points related supplier incoming material problem can be addressed a systematic approach to manage supplier quality.  Supplier quality management (SQM) is a crucial activity for any business that relies on suppliers to provide their goods and services. It involves managing supplier's to deliver product which fulfill customer's needs on time consistently to the agreed quality specification .

Correct Mind Set to Problem Solving

One of the most powerful ingredient to achieve consistent good quality would be the organization positive mindset starting from top management.  There are many quality/six sigma and lean tools created over the past century to assist in problem solving which enable company to achieve their quality goal.   In order to apply lean or six sigma/quality tools successfully to achieve consistent good quality product and bring value to customer,  the whole organization must have the positive mindset and require discipline system starting top down. 

The role of organization leader is very important in cascading positive mindset to the organization team members top down follow follow the law of gravity.   Leadership layer in management of an organization must have clear awareness of  problem and potential problem and risk.  Only from awareness of the problem, then action plan can be established to address the problem followed by carefully orchestrated execution of the plan to successfully resolve the problem.  A problem which get the management attention gets resolve faster than problem which is being hidden in the shop floor. 

Dr Deming (1900-1993) 14 points for total quality management required the top leader involvement in implementation.  In lean enterprise,  top management must not be too far away from the day to day problem.  Leader in an organization are suppose to do a regular gemba walk on the production floor or where the activity of transforming input part to final product happen.  Gemba walk is not just about walking the shop floor,  gemba walk must be designed with objective of eliminating waste which include quality related problem. 

A lot organizations had hire the best people  which will definitely help to bring an organization quality goal to reality however the best talent cannot function alone.  The best people can provide creative solution based on their knowledge and skill set,  they will need the team to mobilize the plan solution then only problem get resolve and goal get realize.  The biggest authority to mobilize a team to execute a plan would be the top management.  Before the mobilization of the plan happen, mobilization of mind had to happen. 

Only with positive open mindset, then the organization will be open to learning new quality methodology and applied what had been learned.  Applying all quality tools will be painful initially as it would mean changes and change is painful to an average human being.    Accepting the changes would require a positive mindset.  The reward come after change would be great and unfortunately most people are only hoping for the reward without willing to pay the price of change.

Validate an Improvement in Key Quality Characteristic

Let’s say we put in a lot effort to reduce all the variations in process input,  the next question would be how do we know if we have really improve the key quality characteristics.

To begin with, we must be able identify what is the key quality characteristic to the consumer and if the key quality characteristic is measurable.  We cannot manage what we cannot measure (Deming, E.W).  Do not jump into improving process yet before collecting the current performance of the key characteristic.  Once the current performance is known such as yield rate of certain quality attributes or process capability of the quality variables,  then improvement effort can kick start.  This is follow by data collection again to gather data on quality performance index after improvement. 

In relation to our above question,  we will need to compare before and after improvement plan data to validate if there is real improvement.  This mean we will need to check  if there is any real shift either in variation or mean of the process.

Shift in process center and variation

Shift in process center 

We have to test our hypothesis that process output quality had improved using statistical hypothesis testing check if null hypothesis, Ho or alternate hypothesis, Ha is valid.  Ho usually state that there is no change in status quo or there is NO change in process output quality and Ha state there is a change in process output quality.  It is also known as comparative statistics method.  In this technique we can compare the following :-

1. Variable data process center such as mean/median before and after improvement
2. Variable data variation before and after improvement - ANOVA
3. Attribute data mean before and after improvement.

Although statistical computer software had made this technique become simple with a few press of button to get the analyzed results,  unfortunately this technique is not widely used or it is not deployed correctly.  It could be due to :

1. Sample size is not sufficient to detect if there is a shift in the process
2. Sample does NOT represent actual population
3. Data measurement process is not validated or corrected
4. Do not use the correct test
5. Do not know how to interpret the results
6. Do not check whether the data is normally distributed
7. Do not understand the concept of confidence interval which is use to estimate the population attribute in process center and variation.

Statistical comparative methods is a very important technique in decision making such as before making a huge investment to change process.  It is the technique to check whether there is a real improvement being made and couple with statistical process control it can also determine if the improvement is sustainable.  This is especially critical in high volume mass production environment where it is not possible to measure every single output and yet we have to ensure every single piece in whole population is consistently good quality.

You can learn more about SPC and process capability through my courses,  Click on the image below to link you to the course.

How to Determine Process Inputs which have an Impact on Process Output

If you had been following all the articles in this website,  you would have already know that there are 6 types of process inputs, Xs  (man, machine, method, material, measure and environment) which could impact a process output/s, Y/s.   However all the 6 process inputs do not impact process output Y in the same magnitude.

There are some process inputs could have very minimal impact while other process inputs could have more influence to the process output.  In turn each process inputs could have its own numerous factors which could impact key output parameters to customers.  

Process input	Examples of factors
Man	Operator training, experience, skills, type of training program,  skill of trainer, management direction etc
Machine	Machine brand, setting of various parameters, level of automation
Method	Work instruction clarity, creator of work instruction, process step and layout, skillset of engineer
Material	Different vendor, different batch, raw material,  manufacturing variation contributed by 5M 1E
Measure	Measurement instrument, measurement method,
Environment	Humidity, temperature, pollution , seasons etc

In order to achieve consistent quality products as perceived by customer, manufacturers must be able to find which vital few factors from each process input/s has/have  major effect on the process output and then control the setting those factors.

The best methodology  to determine which process input factor/s which the most influence on process output which are key to customer would be design of experiment (DOE) .  DOE is a systematic planning and conducting a series of experimental runs in which controlled changes are made to inputs in order to observe and identify causes for changes in the outputs of a system or process. 

DOE methodology consist of the following steps using a good statistical software such as minitab or JMP :-

1. Define  - Understand the quality related problem, identify the key parameters output to customer known as responses, Y.  Use skills and experience to map to the potential input X
2. Design -  Select process input X and  set process input X to high and low setting (level), and design the experiment according to number of factors and setting levels
3. Conduct 1^st experiment  – Verify measurement system for process output measurement (refer to this article and what is measurement system verification http://www.360qualitymanagement.com/2017/09/importance-of-performing-gage.html).  Run experiment according to design and collect data on process output
4. Analyze – Develop a prediction model to estimate the effect of process input factor, X to process output Y.  Identify the potential process input factor which have significant effect on process output Y
5. Optimize throught 2^nd or more experiment  – Fine tune the model to optimize the setting of the process input X to get the best results for process out put Y through prediction modeling
6. Validate through another series of experiment -  Validate the optimum setting and measure process output Y,  Check if the actual results against prediction results.

So far I have not really met any real DOE expert in computer component manufacturing industry which  I have deal with,  and  there are many processes had never been able to optimize their output,Y, due lack of expertise to really understand and able to conduct a true DOE.  I have seen many pitfalls in design of experiment in the following areas :-

1. Trial and errors,  wild guess methods had been mistaken as DOE method
2. Unable to measure process output correctly and there are measurement error associated to measurement process
3. Do not separate controllable and uncontrollable factors
4. There are no real modelling been done to be able to conclude which parameter.
5. Did not use statistical software to do prediction modeling
6. Use the wrong prediction modeling such as process output with binomial distribution (yield rate pass or fail) should use Logistic binary regression
7. Sample size for DOE is not big enough to predict experimental errors contribution in an experiment.
8. Do not understand how to analyze interaction effect between factors.
9. Jump into conclusion after running the 1^st experiment and did not do consecutive experiments such as reduction, optimization and validate all the findings.
10. The actual model did not fit prediction model and there are no attempt to understand why the model did not fit such as the factors X selected does not have impact on response Y or  the impact of controllable factor is more than controllable factor.

Design of experiment is a very powerful tool which enable a manufacturer to understand, optimize and control the vital few process inputs, X to obtain a desirable process output, Y.  This require systematic approach to define, conduct and analyse the experiment and its results under the supervision of a DOE expert.

Why Traditional Statistical Process control Monitoring does not work anymore – Part 2

International Quality Institute in US had innovated the SPC monitoring techniques known as short run SPC to address the needs of current production line with low volume high mix.   In this technique, one chart can be used across different models with different process center and control limits such as part A, B and C shown in chart below.

Short run SPC method transform data collected and can use predetermined the control limits to enable different process center and even standard deviation product can be plotted in one chart.  This is applicable for 

1. Same model product  with different lot to lot process center 
2. Different model product with different process center

There are 2 types of data transformation in short run SPC to get the plot points

1. Target method - Calculating actual measurement readings and calculate the deviation from target point (either using specification or process control) for average chart
2. Standardized method - Nominal transformation of actual measurement data to plot point for both average and range chart.

Unfortunately short run SPC is still not a widely used technique especially in the world of electronics part manufacturing which could due to lack of true quality engineering expert.  There is also limitation in software as currently there is only one commercial statistic software which is capable of plotting short run SPC, Stat soft Statistical.   

It is imperative to be able to monitor the critical quality parameter correctly to ensure that product  quality parameter is reflecting the actual product quality per customer requirement which is the method to consistently good quality product.  Short run SPC is one of the techniques that work in high complexity low volume environment.

Appreciation notes  :  I would like to thank my mentors in Dell who had introduced me to short run and enable me to go further in my journey of SPC discovery  and share with my audience.