Stastistical process control – Basic
Scope
Statistical process control (SPC) is a method of quality control which uses statistical methods. SPC is applied in order to monitor and control a process. Monitoring and controlling the process ensures that it operates at its full potential. At its full potential, the process can make as much conforming product as possible with a minimum of waste. SPC can be applied to any process where the conforming product’s output can be measured.
Stastistical process control – Advance
Scope
Statistical process control (SPC) is applied in order to monitor and control a process. SPC can be applied to any process where the conforming product’s output can be measured.
SPC-Advance course is a follow up of SPC-Basic course. This course will expand fundamental understanding of SPC by getting knowledge of new tools & methods, which will be covered in this course
Problem Solving Techniques 7 QC Tools
Scope
The course is designed based on a proven problem solving model; known as PDCA (Plan-Do-Check-Act). 7 QC Tools are to be applied at different stages in the PDCA cycle. 7 QC Tools has been proven effective by Japanese Quality Guru Mr. Karou Ishikawa and he believed that more than 95% of the problem in a company can be solved by using 7 QC Tools. The Basic Seven Tools made statistical analysis less complicated for the average person. Good Visual Aids make statistical and quality control more comprehendible. QC tools are the means for collecting data, analyzing data, identifying root causes and measuring the result. Users have to develop the solution & implement.
Measurement System Analysis
Scope
A Measurement system analysis(MSA) is especially designed experiment that seeks to identify the component of variation in the measurement any time you measure the results of a process you will see some variation. This variation comes from two sources: one, there are always differences between parts made by any process, and two, any method of taking measurements is imperfect—thus, measuring the same part repeatedly does not result in identical measurements.
Measurement system analysis (MSA) is concerned with identifying sources of part-to-part variation, and reducing that variation as much as possible to get a more consistent product. But before you do any MSA analyses, you may want to check that the variation you observe is not overly due to errors in your measurement system.
MSA is an important tool of Six Sigma and other quality management system
Failure Mode & Effect Analysis (FMEA)
Scope
Failure Mode and Effects Analysis (FMEA) is a tool that examines potential product or process failures, evaluates risk priorities, and helps determine remedial actions to avoid identified problems. An FMEA is a form of Brainstorming that generally follows a Cause and Effect Analysis or a Process mapping and it is usually followed by a Pareto Analysis. It is a granular analysis of a process, a system or a product design for the purpose of identifying possible deficiencies. It is generally conducted by a cross functional group with all the participants having a stake or knowledge about the process, system or product being assessed.
DOE (Design of Experiments) – Basic
Scope
DOE is a structured statistical approach to improve a product/process performance. In DOE with a small number of experimental runs & very large data, significant improvements to process can be made.
DOE (Design of Experiments) – Advance
Scope
DOE is a structured statistical approach to improve a product/process performance. In DOE with a small number of experimental runs & very large data, significant improvements to process can be made.
DOE aids in improving product performance, develops efficient processes, quickly solves manufacturing problems, and assists in breakthrough discoveries by applying powerful statistical methods. A must for Six Sigma, DOE helps you find product and process performance levels where all process requirements are met at minimal cost. For additional information on Process Technologies’ approach to DOE.
Reliability Engineering
Scope
The probability that a component or an equipment or a system performs its intended function for a stated period of time under specified operating conditions.
In today’s competitive world, reliability of equipment is extremely important to maintain quality and delivery deadlines. This is achieved by using proper maintenance and design changes for unreliable subsystems and components of a complex system. It is significant to develop a strategy for maintenance, replacement and design changes related to those subsystems and components. An analysis of down time along with causes is essential to identify the unreliable components and subsystems
Root Cause analysis
Scope
This course will enable participants to understand root cause analysis as a procedure for ascertaining and analyzing the causes of problems in an effort to determine what can be done to solve or prevent them. Consisting of lectures, practice, and role-playing, this course is designed to provide attendees with an in-depth understanding of how to analyze a system to identify the root causes of problems.