Measurement System Analysis and System Thinking in Six Sigma: How They Relate and How to Use Them

Introduction

Since data is the driving force in today’s society, it impacts everything in daily living. Data is used by organizations in millions of ways, such as collecting data in massive loads to measure and inspect. Since organizations base their decisions on measurements, they are important. Also, in any establishment, measurement systems are important. The quantification of specific characteristics is enabled by this system that relates measures. To validate a particular unit of measure, gages, software, and personnel are required. Measurement method, measurement process, measurement instruments, and reference standards are included in the system. Decisions regarding the services provided by an organization are based on measurement values. With unreliable measurements, mistakes and bad decisions are made. More accurate measurements mean fewer errors that will occur in future processes. To assure accurate data, processes have to be suitable to their application (Little, 2001; Galli, 2018c; Milner, 2016; Detert, 2000; Zelinka & Amadei, 2019).

However, measurement systems are from perfect, and there can never be a system completely free of error. There can be small errors that will be mostly insignificant and big errors that can be useless because they are unreliable. Process, such as a test method, personnel including operators and their skill level, equipment’s gages and their calibrated system, items measured their sample plan, and environmental factors, such as temperature and humidity are different sources of variation.

A method of determining the amount variation that exists within a measurement process is measurement system analysis. The overall process variability is directly contributed by measurement process. The system’s accuracy, precision, and stability are evaluated by the method that certifies the system based on its findings. Components of measurement system variation are outlined in Figure 1.

Figure 1.

Components of measurement systems

A methodology that helps to improve an organization's processes by using statistical analysis is Six Sigma by translating operational problems into statistical problems. To solve these problems and to transform the results into practical actions, statistical tools are used (Pourdehnad & Robinson, 2001; Andersen, 2014; Galli, 2018b; Loyd, 2016; Nikabadi & Hakaki, 2018). With a data-driven and greatly methodical approach, defects are eliminated. This method can be used on any organization process in any field. Also, to determine what can be defined as a Six Sigma defect, client specifications are used. Diminishing the inconsistencies in an organization processes is the target. To achieve true Six Sigma, 34 million opportunities is the maximum to be kept by organizational processes. Six Sigma is a business strategy that seeks to identify and eliminate causes of errors or defects-defined as anything that could lead to customer dissatisfaction (Azar, 2012; Antony, 2004; Al-Kadeem et al., 2017a; Galli, 2018a; Nabavi & Balochian, 2018). A very important reason why establishment of Six Sigma is significant is reducing defects.

To identify problem areas and recurring issues that affect quality expectation, employees use certain techniques. With proper training of Six Sigma, employees have the skills to identify problems that affect production or performance. In turn, this helps to identify areas for improvement and can be worked on continuously. With Six Sigma, the variations and waste that appear after improvement ideas can also be eliminated.