Framework for continuous improvement of production processes

Jevgeni Sahno, Eduard Shevtshenko, Tatjana Karaulova, Khadija Tahera

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section.

Original languageEnglish
Pages (from-to)169-180
Number of pages12
JournalEngineering Economics
Volume26
Issue number2
DOIs
Publication statusPublished - 2015
Externally publishedYes

Fingerprint

Failure modes
Costs
Classifiers
Engineers
Monitoring
Six sigma
Continuous improvement
Production process
Industry
Experiments
Six Sigma
Failure modes and effects analysis
Key performance indicators

Cite this

Sahno, Jevgeni ; Shevtshenko, Eduard ; Karaulova, Tatjana ; Tahera, Khadija. / Framework for continuous improvement of production processes. In: Engineering Economics. 2015 ; Vol. 26, No. 2. pp. 169-180.
@article{3bffd3d072944422865c73d987a85e5c,
title = "Framework for continuous improvement of production processes",
abstract = "This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section.",
keywords = "Cost Weighted Factor for Risk Priority Number (CWFRPN), Failure Classifier (FC), Failure Cost Calculation (FCC), Failure Mode and Effect Analysis (FMEA), Process/Product Sigma Performance Level (PSPL)",
author = "Jevgeni Sahno and Eduard Shevtshenko and Tatjana Karaulova and Khadija Tahera",
year = "2015",
doi = "10.5755/j01.ee.26.2.6969",
language = "English",
volume = "26",
pages = "169--180",
journal = "Engineering Economics",
issn = "1392-2785",
publisher = "Kauno Technologijos Universitetas",
number = "2",

}

Framework for continuous improvement of production processes. / Sahno, Jevgeni; Shevtshenko, Eduard; Karaulova, Tatjana; Tahera, Khadija.

In: Engineering Economics, Vol. 26, No. 2, 2015, p. 169-180.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Framework for continuous improvement of production processes

AU - Sahno, Jevgeni

AU - Shevtshenko, Eduard

AU - Karaulova, Tatjana

AU - Tahera, Khadija

PY - 2015

Y1 - 2015

N2 - This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section.

AB - This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section.

KW - Cost Weighted Factor for Risk Priority Number (CWFRPN)

KW - Failure Classifier (FC)

KW - Failure Cost Calculation (FCC)

KW - Failure Mode and Effect Analysis (FMEA)

KW - Process/Product Sigma Performance Level (PSPL)

UR - http://www.scopus.com/inward/record.url?scp=84928678613&partnerID=8YFLogxK

UR - http://inzeko.ktu.lt/index.php/EE/index

U2 - 10.5755/j01.ee.26.2.6969

DO - 10.5755/j01.ee.26.2.6969

M3 - Article

VL - 26

SP - 169

EP - 180

JO - Engineering Economics

JF - Engineering Economics

SN - 1392-2785

IS - 2

ER -