APQP&PPAP: Understand the purpose, principles, process and methods of APQP; master APQP knowledge and skills, be able to effectively carry out project management, and have the ability to serve as a new product development project team leader; explain the content, requirements, internal logic, implementation steps and methods of PPAP in a targeted manner, thereby helping learners truly treat PPAP as a tool that project personnel must master.
FMEA Failure Mode and Effects Analysis (new version FMEA): Combined with IATF 16949:2016 standard and automotive product engineering practice, introduce relevant requirements for automotive industry risk analysis, and deeply understand the latest 7-step requirements of the 2019 new FMEA manual. Understand that FMEA is an important process of product and process development, not just a quality tool. The course mainly promotes the Excel FMEA solution developed by TÜV SÜD, and combines current FMEA software solutions. Through exclusive cases, learners understand and master best practices of DFMEA, PFMEA and FMEA-MSR, audit points and new-format conversion strategies, and strive to help enterprises complete the transition between old and new FMEA standards at the lowest cost.
SPC Statistical Process Control (Second Edition): Understand the basic principles of SPC; understand process variation and its evaluation methods, and master basic statistical concepts and basic steps of SPC.
MSA Measurement System Analysis (Fourth Edition): Define measurement systems and understand measurement system variation and its sources; determine the scope, resources and personnel requirements of measurement system analysis and formulate analysis plans; have basic computational ability to evaluate bias, stability, linearity, repeatability, reproducibility, accuracy and precision existing in measurement systems; through measurement system analysis, improve the ability to select, maintain and improve the effectiveness of measurement systems; meet the requirements of IATF16949 and MSA manual, etc.

• Understand and master the purpose, principles, process and methods of APQP, and have the ability to serve as a new product development project team leader
• Master the content, requirements, implementation steps and methods of PPAP
• Deeply understand the requirements of the new FMEA 7-step method and master best practices of DFMEA, PFMEA and FMEA-MSR
• Master the basic principles of SPC and process variation evaluation methods
• Master MSA measurement system analysis methods and improve the ability to select, maintain and improve the effectiveness of measurement systems
• Meet the requirements of IATF 16949 standard for the five core tools

• Quality managers, project managers, engineers and other personnel directly involved in new product or new manufacturing process development, process standardization, etc.

• APQP overview
• APQP stages: APQP and IATF 16949 planning and project determination
• Product design and development; process design and development
• Product and process confirmation; changes in APQP Second Edition
• PPAP definition, scope and purpose, submission levels, submission content
• Part Submission Warrant (PSW)
• Requirements of new PPAP (Fourth Edition), continuous improvement
• Application of FMEA risk analysis technology in the automotive industry
• FMEA foundation, concepts and terminology
• Analysis of changes in the new standard
• Interpretation of conversion strategy and its impact on IATF 16949 audits
• DFMEA best practices and case analysis
• FMEA-MSR best practices and case analysis
• PFMEA best practices and case analysis, P-diagram robust design
• Introduction to FMEA software solutions
• Relationship between MSA and other core tools and IATF 16949
• Statistical characteristics of measurement systems
• Gauge resolution
• Bias, linearity and stability
• Repeatability and reproducibility analysis
• Analysis methods for attribute gauges
• MSA for complex systems
• Using Minitab software for MSA to improve operability and ensure effectiveness
• SPC Statistical Process Control (Second Edition)
• Brief history of SPC
• Basic principles of SPC
• Statistics and the seven major quality tools
• Variable control
• Attribute control
• Process capability analysis
• Solving non-normal distributions
• Case study
• Course and learner evaluation