Quality Tools and Their Applications in Industry

Quality Tools and Their Applications in Industry

Ana Maria Ifrim, Cătălin Ionuț Silvestru, Mihai-Alexandru Stoica, Cristina Vasilica Icociu, Ionica Oncioiu, Marian Ernuț Lupescu
Copyright: © 2023 |Pages: 11
DOI: 10.4018/IJIDE.325068
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Almost all quality improvement methods require data collection and analysis to solve quality problems. The combination of six sigma and agile creates a six sigma agile methodology that aims to reach quality levels according to the Six Sigma requirements of 3.4 defects per million measurements. In order to achieve these objectives, it is necessary to know the industry well and implicitly the product or the analysed process. Thus, the correctness of these analyses depends on the collection of the data that will be analysed. The use of data analysis methods at each stage, especially in the measurement and analysis stages, is critically important for making strong decisions. The purpose of this article is to present the added value of the integration of six sigma and agile methodologies for IT projects. Thus, the integration of the two methodologies will lead to faster decision-making without the risk of an increase in the number of failures.
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Introduction: Quality Tools And Their Applications In Industry

Companies strive to develop and be sustainable in order to face all challenges (Stojcic et al., 2018). Thus, they implement effective continuous improvement methodologies such as Six Sigma or Agile, which assume the improvement of the existing model at the company level and lead to an increase in the company's ability to reduce the number of timely responses to possible risks that may arise. The concept related to the process model starts from the very simple principle that the organization itself represents a process or, rather, a series of coherent and interconnected processes, which allow the creation of a product that satisfies the client and other interested parties (Womack & Jones, 2006; Schwab, 2016).

Based on the definition of the process, presented in Figure 1, the raison d'être of an organization is to transform with the help of coordinated activities, and input data into output data at the same time as bringing added value to each individual process.

Figure 1.

The general model of a process


Research Methodology

The main objective of the proposed model is the integration of the concepts of Six Sigma and Agile. The proposed research methodology, from a quantitative but also a qualitative point of view, requires a practical approach as well. Quantitative methods were applied for statistical calculations of process performance measurement during the application of Six Sigma projects and the interpretation of the data from the collected questionnaires. Qualitative methods were applied to analyze a wide range of specialized literature in order to propose a new model that integrates Six Sigma and Agile methodologies (Black & Revere, 2006; Chang et al., 2012; Chen et al., 2005).

Six Sigma is a strategy for continuous process quality improvement used in many fields of activity. In general, Six Sigma is a process improvement methodology that reduces product defects, minimizes process variations and improves capabilities in manufacturing processes. Six Sigma offers two major perspectives: One is the statistical perspective, and the other is the managerial perspective. From a statistical point of view, the term Six Sigma is defined as having less than 3.4 defects per million products made or a success rate of 99.9997% (Figure 2) (Pande & Holpp, 2002; Pande et al., 2000; Pande et al., 2002).

Figure 2

The normal distribution in the context of six sigma


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