Systats Consulting Sdn. Bhd.

Acceptance Sampling Plans : Organizations must have some method for minimizing the total cost of inspecting from incoming, intermediate and outgoing product inspections and at the same time not jeopardize quality of product reaching the production line or the customer. One of the alternatives that exist for 100% inspection of product is Sampling Inspection, also known as Acceptance Sampling. The purpose of Acceptance Sampling is to determine the disposition of goods or services (accept, reject or screen). This is done by selecting the disposition that minimizes the cost of inspection to achieve a desired level of quality.

Advanced Data Mining : For the sake of simplicity we often deal with problems one variable at a time. However, the world we live in is more complex with many inter-related processes. In short, the world is multivariate. This course introduces the participant to basic types of analysis for multivariate data. This will enable one to deal with correlated data, explore many variables simultaneous and provide a more complete characterization of processes.

Advanced Design of Experiments Includes Response Surface Methodology : This course explores how experimental design, can be applied to the product and process optimization phase of development. Using Response Surface Methods, models that relate the process outputs to the process inputs are generated. These models allow one to determine optimal settings for the process and identify "sweet spots" that enable the process to the robust to uncontrollable variables. Also included in this course are certain real-life difficulties with running experiments. For example, it is difficult for production to randomize hard-to-vary factors such as oven set-ups requiring stabilization or more...

Advanced Statistical Process Control : The primary objective of SPC is to control and reduce variation in a process. SPC taught in most introductory to intermediate courses showing how to implement SPC under restrictive text-book conditions. However, in the real world of manufacturing many of the text-book conditions frequently break down. Advanced SPC shows how to apply SPC in situations where the standard text-book conditions break down, viz, cases where batch processes occur, situations where data are correlated, existence of fixed effects instead of random effects or where the data are not normally distributed. Advanced SPC also shows how to identify and quantify the various more...

Basic Data Mining Multi-Vari Studies : In todaya ™s data rich age, vast amounts of data are routinely collected. These are termed a happenstancea ™, a non-experimentala ™ or a observationala ™ data. The role of statistics with such observational data is to extract all available informationa often called Data Mining. Equally important is to design the right sampling plan to afford the right data in order to extract information which will allow critical sources of variation to be identified, as well as, to the extent possible, highlight significant relationships between inputs and outputs. The researcher can then use statistical methods much like a detective more...

Basic Design of Experiments : Design of Experiments is an off-line quality improvement technique that can be employed to dramatically improve industrial products and processes. Through its use, it is possible to isolate the cause and effect linkages between product/ process variables and the resulting output measures of function , quality, cost and performance.

Experimental Designs for Mixtures and Chemical prosesses : Special design of experiment design and analysis should be done when factors are dependent as in case of mixtures. Participants are prepared to understand the concept of a mixture and basic statistical models for fitting and analyzing mixture experiments. The focus is on application of mixture experiments to manufacturing operations involving chemical processes. An introduction to basic designs such as simplex centroids, simplex lattice and extreme vertices along with process constraints are presented.

FMEA Failure Mode Effects Analysis : FMEA is a systematic approach that applies a tabular method to aid the thought process used by design and manufacturing engineers as well as other manufacturing personnel to identify potential failure modes and their effects on product, design and processes. This analysis is used to identify trouble areas in product, design or process, assess the impact or risk of the problem, identify solutions that will greatly reduce the negative effect in the design or process, and to determine methods or techniques to prevent the problems. Participants working in teams from the very beginning of the course will have the opportunity to perform an FMEA `livea ™ on a process of their choice.

How to Effectively Use DataGraphs in Presentations : Being able to convince others or to be effectively communicate ideas and results are important skills and activities within business and research. This course will show participants how to select the appropriate graphical tool to achieve a clear and convincing presentation. Participants will be equipped with the knowledge and skills to know what is the most appropriate graphical technique to clearly communicate statistical ideas, how to construct the appropriate graph and how to interpret the graph effectively.

How to Implement a Maverick Lot Program : Deliver high quality product to customers demands that the product be produced under stable conditions. In addition to being in-control, Maverick lot detection is a method to find lots that have been produced under atypical conditions. Although these lots may be within specs, they are suspect and could provide quality or reliability problems to the customer. Maverick Lot detection enables these lots to be flagged and properly dispositioned before customer issues develop. The method can also be used as a way of targeted or "smart" inspection. Participants will know how to detect a Maverick lots, so that the appropriate actions can be taken to prevent customer problems.

How to Measure and Improve Inspection Processes : Inspection is still a necessary and vital part of a wide variety of industries. Yet, the effectiveness of such inspections is usually not carried out in a rigorous manner. This course presents an easy and comprehensive way to asses and improve inspection processes and uses a complimentary Excel routine written especially for the analysis of attribute gauge studies. Participants will be able to plan an attribute gauge study for assessment of an inspection process. Methods outlined in ISO standards are presented along with an in-depth use of Kappa statistic will be interpreted by participants to target how to improve the inspection process.

How to Optimally Adjust Processes to Maintain a Target Value : Traditional SPC concentrates on separation of common from special cause but is not meant to be a process adjustment scheme. However, in many manufacturing applications, control to a target is of primary concern. This course gives engineers the knowledge to know when adjustment is necessary, what kind of adjustment to make, and to design optimal adjustment schemes in terms of deviation from target along with minimization of cost. Participants will be able to set process targets, design and implement an adjustment scheme to control the process to a target value.

How to Plan Statistically Valid Research or Engineering Evaluations : Many industrial processes have complexities that can sometimes result in incorrect decisions costing large sums, In research, incorrect or poorly planned experimentation can results in papers rejected., lost time and lost money. In both cases methods exist to plan meaningful experiments and evaluations to minimize time to solution and resources while still providing cogent arguments for making second judgments. Avoid the unintentional "statistical lie" Participants will be able to pair proper experimental technique and strategy to the given situation. Participants will learn common pitfalls of experimentation and recommend appropriate experimental plans.

How to set Process Specification Limits : The creation of specification defines processes. It is critical that these processes boundaries be set accurately based on data and sound analysis. This HOW TO SERIES provides proven techniques to statistically valid process specification limits or to reexamine current process specifications for validity. This is vital knowledge that every engineer, manager, R&D member or researcher should know. Participants will acquire strategies to set meaningful spec limits to achieve better customer satisfaction and internally validity.

How to Use EVOP to Fine-Tune Processes During Production : Industrial processes usually are not operating at optimal performance due to many small adjustment, wear, age, deterioration, replacements of parts, and a myriad of other causes. Evolutionary Operation(EVOP) collects information DURING production to optimize the process real-time resulting in continued optimal performance. Heavily used in Chemical settings but also with widespread applications in many process industries. Participants will be able to implement EVOP in production to not only produce a product but simultaneously produce information to optimize the process performance.

How to Write and Review Technical Reports : To review and write reports well not only impacts the company, but also aids in the advancement of the engineer, manager or researcher. Like two sides of the same coin, writing and reading technical reports compliment each other. Thus, the first part of this module presents Strategies for writing effective engineering reports, specifications, and research papers. Then the second part shows how to review technical reports using four necessary conditions to accept a conclusion. Participants will learn effective strategies to improve their engineering, research and specification report writing and critiquing skills

Intermediate Data Mining : Often in process control and improvement efforts, one is called upon to solve problems involving sets of variables where it is known that there exist some inherent relationship among the variables. Regression Analysis is a statistical technique to model the relationships between two or more variables. Use of regression analysis includes quantitavely describing relationship between a particular variable and another set of variables, determining the important process variables, locating the optimum operating conditions and forecasting and prediction.

Lean Six Sigma Manufaturing Green Belt and Black Belt Program : This program is a combination of Lean Six Sigma Green Belt and Black Belt programs. Lean Six Sigma adds more lean tools to focus more on lead time reduction, cost reduction and waste elimination. The four-week training is organized around the five main phases of the Lean Six Sigma Roadmap: Define, Measure, Analyze, more...

Measurement System Analysis I Gauge RR for Variables and Attribute Data : Fundamental to collecting data on any process or equipment is a characterization of measurement. Data, which do not come from an accurate measurement system, may lead to erroneous conclusions. This course provides the participants with an understanding of basic measurement process terminology including discrimination, bias, accuracy, precision, repeatability and reproducibility. It provides the methodology to plan, conduct, analyze and interpret measurements system capability study, which includes a gauge repeatability and reproducibility (R&R) study and determination of measurement systems uncertainty. Changes reflected in the QS9000 MSA revision 3 reference manual are incorporated into this course.

Measurement System Analysis II : This course provides the participants with further in-depth understanding of more advanced MSA techniques. Bias and Linearity studies using hypothesis testing are explored. In addition, it also provides specific analysis for various problems related to measurement systems, e. g., use of ANOVA methods for Gauge R&R, comparison of gauge, and the Kappa statistic for use in attribute gauge studies. This course incorporates the changes reflected in the QS9000 MSA revision 3 reference manual.

Multivariate Statistical Process Control : Statistical Process Control is most often implemented on one variable at a time. However, with modern methods of data collection tens, hundreds, or even thousands of variables are measured and data logged. Trying to control variables one at a time ignores possible correlation between variables exposed giving to more meaningful and sensitive process control. Any industries with measurements on many input or output parameters will profit from knowing the benefits of Multivariate SPC methods.

QFD Quality Function Deployment : QFD is a systematic approach to achieving superior Customer Service and Quality of Design in the product development cycle. It listens to the voice of the customer in order to understand the wants and needs of the customer and then translates these into concrete internal specification or actions. QFD is a planning, communication, and documentation tool that determines where energy, effort, quality improvement tools and technology need to be applied in order to sustain the overall product plan or improve customer satisfaction.

Reliability Availability Maintainability : Basic information for analysis and reliability are presented. Metrics are presented and methods for modeling developed. Applications are given to setting PM schedules, analysis of downtime, repair versus replacement costs and prediction and demonstration of performance. Participants will understand basic ideas and measures of reliability, availability and maintainability in addition to be able to form models for prediction and demonstration of performance.

Robust Design for Manufacturability : Building processes that are not easily affected by noise or processes that transmit minimal variation from the inputs to the output produce savings in cost and improvement in quality. This short course introduces methods to determine settings of combinations of controllable factors that minimize the variation of a response in the presence of variation introduced by controllable and uncontrollable variables. The contributions of Genichi Taguci are central to an understanding of design for robustness. Taguchis ideas are then integrated with traditional DOE design and analysis to produce a method for achieving process robustness.

Root Cause Analysis and Problem Solving : Problem solving and decision making are used to resolve a Special Cause problem when the cause of the problem is unknown. It has three different aspects that work together synergistically; viz., a problem solving process, a data driven driven code of conduct and a reporting format. As a Problem solving process, it is a sequence of eight events that should be followed from the moment a problem become evident. When correctly followed, it helps to facilitate a timely and complete resolution to a problem. It is a standard, a code of conduct, based on facts, where problem solving, decision making, more...

Statistical Process Control : This course is specially developed to provide participants in manufacturing industries the basic statistical techniques for process control and improvement. Participants will gain knowledge of the fundamentals of process improvement, concept of variation, statistical control and other simple but powerful statistical techniques. This course puts heavy emphasis on the concepts that motivate and underlie the techniques. The techniques themselves are very simple but must be applied correctly to be effective. From experience, we find that problems of implementation stem from inadequate conceptual understanding of the techniques and sound advice for implementation. This course gives participants the more...

Statistical Thinking for Management : In today's ultra-competitive environment with increased access to multiple sources of information, the edge will go to those firms that are most able to effectively utilize information. The exceptional manager achieves results based on sound decisions made from available information in the presence of uncertainty. Statistical Thinking for Management will take the participants through proven techniques of effective utilization of information using statistical principals. The course is geared to deal with the following five functions of Management: 1) Setting Goals, more...

Survey Design Analysis : Surveys are a common tool in business for gathering data, especially customer information data. This course looks at planning such surveys, possible designs, and survey analysis. Attention is paid to allowing as much information as possible to be extracted from the data, drawing appropriate conclusions from the survey data and using informative methods for presentation of these conclusions.

Time Series Analysis and Forecasting : Of fundamental importance in business planning is the ability to generate a usable forecast. Although time series is most often applied to economic sequences of events, the methodology can be applied to any manufacturing, engineering or research data that are collected over time with a stable input pattern. This course will provide participants with a working knowledge of the applications of forecasting and time series analysis along with a general understanding of the underlying theory. This course combines both theory and application and focuses on the analysis and modeling of a series of events with the object of generating meaningful forecasts.

Weibull Analysis Product Reliability Analysis : Weibull analysis models the relationship between product failures and product reliability. These models can be used to predict future performance and to improve product reliability. A practitioner selects a relatively small number of units for test and makes predictions about a population of such units concerning important life characteristics such as the reliability function, mean time to fail or probability of failure at a certain time. The statistical software used allows for easy distribution fitting for reliability data that may be censored and also to build models that describe and predict reliability performance.

Weibull and Product Reliability Analysis : Weibull analysis models the relationship between product failures and product reliability. These models can be used to predict future performance and to improve product reliability. A practitioner selects a relatively small number of units for test and makes predictions about a population of such units concerning important life characteristics such as the reliability function, mean time to fail or probability of failure at a certain time. The statistical software used allows for easy distribution fitting for reliability data that may be censored and also to build models that describe and predict reliability performance.