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SCRUM Master (PSM 1)

SCRUM Master (PSM 1)

Quick Info

SCRUM is an agile framework for project management that can be used successfully in all industries. It is characterized by short work cycles, self-organizing teams and continuous improvement.

This module teaches the application of SCRUM principles and the development of best practices for the introduction of SCRUM. It also covers the strategic roles in agile project management, dealing with stakeholders and the development team and communicating project progress.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 1
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  • In-house
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  • In the languages:
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- 5
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Contents

● Comparison of PM methods

● Agile Manifesto

● Empiricism

● Transparency

● SCRUM values

● Framework

● Events

● Artifacts

● Roles

● Definition of Done

● SCRUM Board

● CIP in SCRUM

● SCRUM Framework

● Product backlogs

● Release planning

● Stakeholder management

● Create forecast

● Key figures in SCRUM

● Burn Down Chart

● Refinement

Key information

The SCRUM Master is an extremely important and central role in the agile Scrum framework for product development. This person acts as a servant leader and is tasked with helping the Scrum team to work effectively, remove impediments and put the Scrum principles into practice. The Scrum Master plays a critical role in fostering a culture of openness, transparency and continuous improvement by ensuring that the team has the right tools and resources to succeed.
In addition, the Scrum Master is responsible for resolving conflicts, facilitating communication and ensuring that the team is constantly learning and improving. Ultimately, the Scrum Master helps to increase the team’s efficiency, improve the quality of products and maximize customer value by creating an environment in which the team can reach its full potential.

History

The SCRUM Master role was conceived by Jeff Sutherland and Ken Schwaber as part of the Scrum framework, which was developed in the 1990s. It arose from the need to create flexible and agile methods for product development and has since been successfully applied in many industries.

Usage

SCRUM Masters are used in various industries and organizations, from software development teams to marketing and sales departments. They work closely with the Scrum team to ensure that Scrum is applied effectively, obstacles are removed and the team is continuously improved.

 

Benefits

  • ● Promotion of an agile way of working
  • ● Improvement of team communication
  • ● Reduction of obstacles in the workflow
  • ● Continuous retrospectives
  • ● Increasing the productivity of the team
  • ● Strengthening self-organization in the team

Risks

  • ● Conflicts in teams with stakeholders
  • ● Misinterpretations of the SCRUM principles
  • ● Overloading the SCRUM Master
  • ● Problems caused by traditional working methods
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Module-en

Kata Coaching

Kata Coaching

Quick Info

Toyota Kata is a pattern that employees use to approach problems scientifically. In order for employees to adopt the pattern of scientific thinking in all areas of the organization, they must be accompanied by a coach. The problems and optimizations are carried out by the employees themselves through experiments.
This strongly promotes the independence and appreciation of employees within the company. In future, employees will be able to solve many problems independently.

  • Duration:
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  • Next Starts
  • Live webinar dates in:
- 7
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  • In-house
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  • In the languages:
- 9
- 11
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Contents

● Definition of Toyota Kata

● Think scientifically

● Kata in management

● Indirect areas

● Improvement kata

● Coaching kata

● Distribution of roles

● Deming cycle (PDCA)

● Toolbox for kata

● Resistors

● Continuing learning in old age

● Kata projects

● How to get started with kata?

● Kata questions

● Challenge (North Star)

● Kata process

● Kata storyboard

● The role of the coach

● Coach-Coach

● Benchmarkings

Key information

Kata Coaching is a highly effective and systematic method based on the proven principles of the Toyota Kata concept. This method aims to promote continuous learning and improvement by providing structured routines and exercises.
These routines and exercises enable employees to develop their problem-solving skills, optimize processes and establish a culture of continuous improvement. Through the use of coaching techniques, employees are empowered to achieve their goals and overcome obstacles by systematically conducting small experiments and learning from them.
The focus is on the iterative process of planning, executing, reviewing and adapting, which enables employees to continuously improve and adapt to change. Kata Coaching fosters an environment where employees are encouraged to try new ideas, take risks and learn from mistakes, which ultimately leads to innovation, increased efficiency and organizational growth.

History

The Kata method has its roots in lean management and was developed by Toyota. It was originally introduced as part of the Toyota Kata concept, which aims to train managers and employees in the principles of continuous learning and improvement.

Usage

Kata Coaching is used in various industries and sectors, including manufacturing, services, healthcare and administration. It is used to empower managers and employees to achieve continuous improvement by regularly practicing problem-solving techniques and routines.

Benefits

  • ● Promotion of a learning culture
  • ● Verbesserung der Problemlösungsfähigkeiten
  • ● Increased employee participation
  • ● Effective implementation of CIPs
  • ● Increase in process efficiency

Risks

  • ● Resistance to change
  • ● Too rigid application of the method
  • ● Additional tasks for employees
  • ● Measuring the effectiveness of coaching
  • ● No support with the introduction
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Module-en

Shopfloor Management

Shopfloor Management

Quick Info

The term store floor management stands for: “Leading at the point of value creation”. The idea is to bring management closer to the employees.
The aim of store floor management is to make the results of processes in the company transparent. The company goals are broken down into different levels and presented using key figures. This allows problems to be identified more quickly. In this module, you will learn about the elements of a store floor management system and how you can improve through standards, transparency and better communication.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 13
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  • In-house
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  • In the languages:
- 15
- 17
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Contents

● Introduction

● Management levels

● Corporate purpose

● Mission, vision, strategy

● Cascading of objectives

● Hoshin Kanri process

● The X-matrix in the SFM

● Vertical communication

● Leading on site

● Visual management

● Dashboards

● Dealing with key figures

● SQCDP Boards

● CIP boards

● Behavioral key figures

● Behavioral systems

● Task boards

● KANBAN, T-Card

● Qualification matrix

● SFM introduction

Key information

Store floor management (SFM) is an effective management method used in companies to increase efficiency and transparency. SFM focuses on achieving improved performance through direct and continuous leadership on the shop floor. This approach emphasizes the importance of visual control of work processes and encourages the active involvement of employees to establish a culture of continuous improvement.

Through clear visualization of workflows and regular communication, bottlenecks and issues are quickly identified, leading to a faster response and more efficient production overall. SFM allows managers to be directly in the workplace, supporting employees, providing feedback and implementing change in real time. This method promotes an open and transparent work environment where all team members are encouraged to make suggestions for improvement and take responsibility for the team’s success.

History

SFM is based on the principles of lean management and has its roots in techniques originally developed in Japanese companies such as Toyota. These methods were developed specifically for monitoring and controlling workflows at the process level.

Usage

Shopfloor management is primarily used in manufacturing, but is also applied in the service, logistics, healthcare and retail sectors, where clear processes and efficient employee management are required.

Benefits

  • ● Increased employee engagement
  • ● Problems are recognized quickly
  • ● Bessere Kommunikation in allen Ebenen
  • ● Higher productivity
  • ● Good process control

Risks

  • ● Initial effort high
  • ● Management support required
  • ● Key figure systems too complex
  • ● Resistance in management
  • ● Overloading of employees
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Module-en

Design of Experiments

Design of Experiments

Quick Info

Design of experiments is a structured plan for analyzing correlations. The relationships of many influencing factors on a result are examined in order to obtain the best setting of inputs.
In statistical design of experiments, results are not simply evaluated, but an experimental plan is drawn up, which is carried out and evaluated in practice. The experimental design can then be optimized based on the findings. This means that often only very few experiments are necessary compared to other methods in order to obtain the same or even more findings.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 19
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  • In the languages:
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Contents

● Introduction to DOE

● Target size, factor & levels

● Set up experimental design

● Interactions

● Design of experiments analysis

● Significance, p-value

● Target variable optimization

● Max. & min. problem

● Full factorial & partial factorial

● Resolution (resolution)

● Blending of terms

● Replications

● Effect, selectivity

● Reduction of the model

● Residual diagrams

● Central point

● Check linearity

● Block formation

● Overfitting

● Randomize

Key information

Design of Experiments (DOE) is a systematic method that is used in various areas such as research, development and production. It enables the planning, execution and analysis of experiments, whereby the effects of several factors on one or more target variables can be determined simultaneously.

By using DOE, you can understand complex relationships in a system by systematically investigating different factors and their interactions. The main objective of DOE is to identify significant influencing factors and to find optimal conditions for desired results. By varying different parameters and analyzing their impact on the outcome, organizations can make decisions to improve processes.

History

The foundations of DOE were laid by Sir Ronald A. Fisher in the 1920s. Fisher developed the principles of experimental design and statistical analysis to make agricultural research more efficient. Since then, DOE has established itself as an indispensable tool in many scientific and engineering disciplines.

Usage

DOE is widely used in product development, process optimization and quality assurance across various industries, including pharmaceuticals, chemicals, manufacturing and biotechnology. It is used to increase process efficiency, reduce costs and improve product quality.

Benefit

  • ● Understanding of interactions in the process
  • ● Accelerated time to market
  • ● Maximization of product quality
  • ● Minimization of risks and uncertainties
  • ● More efficient process optimization

Risks

  • ● Data distortion due to interference factors
  • ● Complexity of the experiment design
  • ● Incorrect interpretation of the results
  • ● High costs for experiments
  • ● Lack of control over external influences
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Value Stream Management

Value Stream Management

Quick Info

A value stream map is a process flow diagram used to identify problems in a company’s material or information flow. The origin of the VSM can be traced back to Toyota.
In this module, you will learn how to create a value stream map at a strategic level with a cross-functional team. The information and material flows as well as key figures in the VSM are presented as the current status (Current VSM). From this, you derive the future, improved state of your process (Future VSM). You define measures to achieve this new state.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 25
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  • Alternatives:
  • One-to-one coaching
  • In-house
  • Small groups
  • In the languages:
- 27
- 29
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Contents

● Introduction to VSM

● Meaning of value stream

● Types of VSM

● Product families

● VSM Current State

● VSM Future State

● Customer cycle

● Include process chain

● Standards data boxes

● Symbols and levels

● Process efficiency

● Key questions on the VSM

● Kaizen flash

● Process time

● Cycle time

● Takt time

● Display pull / push

● Implementation & maintenance

● Bottlenecks & constraints

● Derive strategy projects

Key information

Value Stream Mapping (VSM) is a highly effective visual method used in product development and production to analyze and improve flows of materials and information. The main objective of VSM is to visualize the entire process chain from raw material extraction to the customer in detail in order to identify and exploit optimization potential.
By clearly visualizing the current state of the value stream, bottlenecks, waste and inefficient processes can be easily identified. In addition, VSM enables a holistic view of the production process, including all relevant information and value creation steps. By analyzing the current state and developing a future state, organizations can implement targeted improvement measures to increase efficiency, shorten lead times and increase customer satisfaction.

History

VSM was developed as part of the Lean Manufacturing philosophy, which has its roots in the Toyota Production System. It is designed to identify and improve inefficient parts of production lines by focusing on creating value for the customer.

Usage

VSM is used in various industries to analyze and improve process flows. This method helps companies to reduce waste and shorten throughput times. It is often used in manufacturing, but also in service and software development.

Benefits

  • ● Visualization of processes
  • ● Identification of waste
  • ● Bottlenecks visible
  • ● Projects can be derived
  • ● Standardization of processes

Risks

  • ● Initially time-consuming
  • ● In-depth understanding of the processes required
  • ● Incomplete analyses lead to problems
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Module-en

Kanban

Kanban

Quick Info

Kanban, translated from Japanese, means “Kan” = signal and “Ban” = card. It is a method from Lean Management used to control the flow of objects through cards. These objects can be products, services, information, or even projects.

Kanban is a fundamental element of the Toyota Production System (TPS). Depending on the objective, we distinguish between Generic Pull Systems, Replenishment Pull Systems, and Kanban. In this module, you will become familiar with the basic function and calculation of Kanban.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 31
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  • In the languages:
- 33
- 35
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Content

● Introduction to Pull

● Controlling Objects

● Kanban Visualization

● Replenishment Pull

● Generic Pull

● Strategies for Implementation

● Inventory Calculation

● Coefficient of Variation (CV)

● Determining Customer Demand

● Process Winners

● Bullwhip Effect

● Forecasts

● Service Level (SL)

● Cycle Time Interval (CTI)

● Safety Stock

● Combine objects

● Information Flow

● Order Triggers

● Warehouse Simulation

● Calculation Examples

Key Information

Kanban is a highly effective lean management method that focuses on just-in-time production and controlling the flow of work through visualization. Originally developed at Toyota plants, Kanban aims to minimize bottlenecks, increase efficiency and ensure continuous delivery by tracking the actual consumption of resources.

At the heart of Kanban is the Kanban board, a visual representation of the work process that allows teams to track the progress of their tasks, identify bottlenecks and respond quickly to changes. By clearly visualizing the flow of work, bottlenecks and overloads become easily identifiable, leading to improved efficiency and faster delivery of products or services.

History

The Kanban method was developed by Taiichi Ohno at Toyota in the 1940s as part of the Toyota production system. It was introduced to improve production efficiency and optimize inventory management by responding to the actual needs of downstream production stages.

Use

Kanban is widely used in the manufacturing industry and increasingly in software development and other service industries. It helps organizations to react flexibly to changes in demand, increase throughput and reduce waste.

Benefits

  • ● Improve transparency in processes
  • ● Effective control of the workload
  • ● Reduction of waiting times
  • ● Optimization of inventories
  • ● Continuous improvement of processes
  • ● Promoting the self-organization of teams

Risks

  • ● Consistent discipline required
  • ● Irregular demand leads to problems
  • ● Variations are not considered
  • ● System must be checked regularly
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Kaizen & A3 Report

Kaizen & A3 Report

Quick Info

The A3 report has its origins in the Toyota Production System (TPS) and is a problem-solving method. It refers to the four phases of the PDCA cycle (Plan-Do-Check-Act), also known as the Deming circle.


8D is also a problem-solving method. Here the D stands for disciplines that should be consistently adhered to. Both methods have the same goal, namely to solve the problem in a structured and methodical way. Kaizen stands for change for the better and describes the mindset. In this module, you will learn how to plan, prepare, implement and follow up Kaizen events.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 37
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  • Alternatives:
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  • In the languages:
- 39
- 41
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Contents

● Kaizen Events

● Prepare event

● Carry out event

● Event follow-up

● Basics (5S / SMED)

● War rooms

● Gemba Walks

● CIP boards

● 8D report

● A3 report

● Prepare reports

● The 8 steps in the A3

● Carry out pilot tests

● Before and after comparison

● Management presentation

● Call to action

● Sustainability of Kaizen

● 3 GENS

Key information

Kaizen and the A3 report are two proven methods in lean management that focus on continuously improving processes and tackling problems systematically. Kaizen, which means “change for the better” in Japanese, focuses on constant, incremental improvements and a culture of continuous improvement. The A3 report, on the other hand, is a structured approach, named after the A3 format of the paper on which the report is created. This method supports the systematic analysis of problems, the development of solutions and the communication of results in a clearly structured way.

History

Kaizen was developed in Japan after the Second World War as part of the Toyota Production System to improve efficiency in production. The A3 report, also developed at Toyota, was introduced as a problem-solving and communication tool to clearly present and process complex problems.

Usage

Kaizen and A3 are widely used in industry, healthcare, education and other sectors that strive for a culture of continuous improvement. They are used to increase process efficiency, improve quality and increase employee participation.

Benefits

  • ● Can be used in business processes
  • ● Improve operational performance
  • ● High employee participation
  • ● Strong customer orientation
  • ● Quick solutions possible

Risks

  • ● Cultural adaptation required
  • ● Management Unterstützung erfoderlich
  • ● Clear communication must be in place
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Module-en

Regression

Regression

Quick Info

Regression is a statistical method for analyzing the relationship between one or more independent variables and a dependent variable. In this module, you will learn to make predictions about the dependent variable by finding a function that best explains the measured data.
It is used in various fields such as economics, medicine and engineering and is based on assumptions such as the linearity of the relationship and the homoscedasticity of the residuals.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 43
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  • In the languages:
- 45
- 47
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Contents

● Natural scattering

● Non-natural scattering

● Stability tests

● Correlation vs. regression

● Forms of correlation

● Correlation coefficient

● Regression analysis

● Coefficient of determination (RQD)

● Regression models

● Linear regression

● Quadratic regression

● Cubic regression

● Residual diagrams

● Forecasts

● Target value optimization

● Overfitting

● Residual vs. adjustment

● Application in practice

Key information

Regression is a statistical tool used to model the relationship between a dependent variable and one or more independent variables. Its main goal is to understand this relationship and make predictions about future observations based on it. Through regression, we can recognize patterns, understand trends and even investigate causalities between variables. It is a flexible and versatile analytical tool used in various fields such as economics, social sciences, medicine and engineering.

History

Regression analysis has its origins in the 19th century, when Francis Galton investigated the concept of regression to the mean to describe biological phenomena. Since then, regression has become a central tool in many scientific, economic and social fields.

Usage

Regression is used in almost every field that requires data-based predictions and decision making. These include economics, finance, medicine, biology, engineering and more. The methodology makes it possible to learn from historical data and predict future trends or outcomes.

Benefits

  • ● Predicting the relationships between variables
  • ● Flexible application
  • ● Identify the strength of influence of the variables

Risks

  • ● Risk of overfitting
  • ● Very good statistical knowledge required
  • ● Ignoring non-linear relationships
  • ● Misleading results
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Hypothesis Test

Hypothesis Test

Quick Info

Hypotheses form assumptions about potential correlations within your data. By using hypothesis tests, you have the opportunity to check these assumptions statistically. They can be confirmed or rejected. Every hypothesis test is based on two fundamental concepts: the null hypothesis and the alternative hypothesis. Both are crucial in determining whether a hypothesis is confirmed or rejected.
As part of this process, you will become familiar with various test procedures that will enable you to analyze your data in a statistically sound way.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 49
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  • In the languages:
- 51
- 53
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Content

● Basic population

● Sample

● Null hypothesis

● Alternative hypothesis

● Confidence interval

● Confidence level

● Significance level

● Probability of error

● p-value

● Test for normal distribution

● T-test & F-test

● Analysis of variance

● Test of proportions

● Alpha error

● Beta error

● Error bar chart

● Sample size

● Selectivity

● Effect

● Practical examples

Key information

Hypothesis tests are statistical procedures used to test assumptions about a population based on sample data. These tests allow researchers and analysts to make decisions about the validity of statistical hypotheses by calculating the probability with which the observed data would occur if the null hypothesis were true.

History

Hypothesis testing was developed in the early 20th century by statisticians such as Ronald Fisher, Jerzy Neyman and Egon Pearson. These methods were created to support scientific research by providing objective procedures for testing theories and hypotheses.

Usage

Hypothesis tests are essential in many fields such as medicine, psychology, social sciences and economic research. They are used to test the effectiveness of treatments, evaluate differences between groups and analyze trends in data.

Benefits

  • ● Well-founded decision-making
  • ● Minimize errors
  • ● Increase scientific credibility
  • ● Recognize (non-)random effects
  • ● Quantifying uncertainties

Risks

  • ● Incorrect interpretations
  • ● Overinterpretation of the p-value possible
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MSA & SPC

MSA & SPC

Quick Info

In this module, you will receive an introduction to the use of measurement systems. You will learn the scattering components of MSA and develop a deep understanding of measurement system analysis. The module guides you step-by-step through the procedures of measurement system analysis (MSA), starting with the basics and moving on to a detailed look at important key figures such as Cg and Cgk for continuous and attributive measurement data.
You will also learn how to use control charts to effectively monitor process behavior. This preventative strategy allows you to proactively intervene in processes to identify and correct potential errors at an early stage or prevent faults from occurring before they manifest themselves.

  • Duration:
Dauer auf Anfrage
  • Next Starts
  • Live webinar dates in:
- 55
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  • One-to-one coaching
  • In-house
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  • In the languages:
- 57
- 59
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Contents

● Basics of MSA

● Variation component

● Resolution

● MSA 1

● MSA 2 (continuous, attributive)

● Key figures (Cg, Cgk)

● Measurement deviation (BIAS)

● Scattering components

● Reproducibility

● Repeatability

● Control chart technology

● I/MR chart

● P-chart

● Linearity, stability

● Sample size

● Warning limit

● Intervention limit

● Specification limit

● Trends in control charts

● Process variations

Key information

MSA (Measurement System Analysis) and SPC (Statistical Process Control) are statistical methods used in quality control to check measurement accuracy and monitor processes. MSA focuses on analyzing the measurement system to identify sources of error such as bias and scatter. SPC, on the other hand, uses control chart techniques to monitor and control process stability and variation.

History

The development of SPC dates back to the 1920s, when Walter A. Shewhart of Bell Laboratories developed the first control charts. MSA was later introduced as a complement to SPC to ensure the reliability of the measurement data used in control charts. Both methods were further developed during the Second World War and in the post-war period.

Usage

MSA and SPC are used in a variety of industries, including manufacturing, automotive, pharmaceutical and other industries where high quality standards are required. These methods help companies to ensure the quality of their products by evaluating the accuracy of measurement systems and continuously monitoring processes.

Benefits

  • ● Improve product quality
  • ● Reduction of variability
  • ● Monitoring of processes
  • ● Ensure the capability of measurement processes
  • ● Recognize trends

Risks

  • ● Ongoing monitoring required
  • ● Qualified personnel required for data analysis
  • ● Less effective in dynamic environments

With more than 4,000 projects and case studies, Alphadi is a leader in the field of Lean Six Sigma and Sales Process Engineering. We advise you holistically so that your goals are achieved sustainably and in the long term.

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