Quality Engineering Techniques from Past to Future

A Discussion on Comparison of Previous Research with the Proposed Model

Of the previous research done on statistical techniques (ST) and non-statistical techniques (N-ST), the research that focused on singular applications in several industries or scientific fields are valuable. Table 5.1, for instance, sheds light on the real path of the research conducted so far.

Not one of the previous research studies has a comprehensive model for implementing QET, in particular, for industrial factories or manufacturing industrial products. Moreover, the process approach for describing the proposed model is the key point of the book.

Figure 5.1 presents the two main approaches for applying statistical and non- statistical techniques from the past to the present.

TABLE 5.1

Path of Research on (ST) and (N-ST) Applications

N

Author(s)

Research title

1

(Sima el al., 2019)

Feasibility of Using Simulation Technique for Line Balancing in Apparel Industry

2

(Tulcidas et al.. 2019)

Statistical methodology for scale-up of an anti-solvent crystallization in the pharmaceutical industry

3

(Ваша et al., 2018)

Chapter 10 - Statistical Techniques in Pharmaceutical Product Development

4

(Andrade et al., 2018)

Application of waves trapping statistical technique to estimate an extreme value in train aerodynamics

5

(Cristovao et al., 2018)

Fish canning industry wastewater variability assessment using multivariate statistical methods

6

(Memon and Shaikh, 2016)

Confidence bounds for energy conservation in electric motors: An economical solution using ST

7

(Lim and Antony, 2016)

Statistical process control readiness in the food industry: Development of a self-assessment tool

8

(Lin et al., 2015)

Identifying water recycling strategy using multivariate statistical analysis for high-tech industries

Trend of two main approaches in the development of QET

FIGURE 5.1 Trend of two main approaches in the development of QET.

A mixture of both ST and N-ST approaches in the form of an integrated model for industrial organizations has not been studied or at least has not been reported. For the first time, such an approach has been considered and applied in this research. Furthermore, several aspects of the proposed model in this book offer new approaches for carrying out systematic studies in industrial organizations.

Final Results of the Research in Manufacturing Industries

Figure 5.2 provides a summary of the main points of the proposed model in this research.

The most creative aspect of this book is the introduction of a process map within the organization, besides exploiting several quality engineering techniques including statistical and non-statistical tools applied to different levels of organization. The most innovative recommendation of this book is to execute the proposed model in an

Proposed model of QET for industrial factories

FIGURE 5.2 Proposed model of QET for industrial factories.

effective format for the defense sectors of the country and to create or increase added values for manufacturing industrial products. The proposed model in this book utilizes several features as follows:

  • • Z-MR control charts for describing the impacts of units on productivity and sustainability
  • • Calculations of the total score of productivity and sustainability before and after implementing the model
  • • Demonstration of the growth in added values for manufacturing industrial products
  • • Generalization of the assessment results of the model to other organizations
  • • Assessment of risks and opportunities with using the model in manufacturing industries
  • • Impacts of implementing the model in industrial economics

Suggestions for Future Research

One of the best suggestions that can be made is to design and implement the proposed model in fuzzy environments in industrial organizations. The fuzzy environments require advanced statistical and non-statistical techniques. Moreover, analytical mathematics must be considered. Furthermore, the uncertainty issue related to different results in statistical calculations is one of the most important points to consider and it seems to be the greatest challenge of the 21st century. The generalization of the proposed model to uncertain situations can be regarded as an attractive project which could change the future of industrial organizations. In the end, it is hoped that the proposed approach can lead to productivity and sustainability through the application of applying QE. The authors hope that the model proposed in this book could open a new door toward achieving superior goals in the industrial world of today.

References

Abbasi, M., Rostamkhani, R., (2014), Reliability Application of Industrial Manufacturing Networks in Outsourcing, Journal of Engineering and Quality Management, Volume 3, No. 4, Pages 247-259.

Andrade, A.R., Johnson, T„ Stow, J„ (2018), Application of Waves Trapping Statistical Technique to Estimate an Extreme Value in Train Aerodynamics, Journal of Wind Engineering and Industrial Aerodynamics, Volume 175, Pages 419-427. https://doi. org/10.1016/j.jweia.2018.02.009

Ваша, A., Deb. P.K., Maheshwari, R.. Tekade. R.K.. (2018), Chapter 10—Statistical Techniques in Pharmaceutical Product Development, In R.K. Tekade (ed.), Dosage Form Design Parameters, Volume 2, Pages 339-362, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India. https://doi. org/10.1016/B978-0-12-814421-3.00010-5

Bounazef, D„ Chabani, C., Idir, A., Bounazef, M., (2014), Management Analysis of Industrial Production Losses by the Design of Experiments, Statistical Process Control, and Capability Indices, Journal of Business and Management, Volume 2, No. 1, Pages 65-72. https://doi.org/10.4236/ojbm.2014.21009 Cristovao, R.O., Pinto, V.M.S., Goncalvez, A., Martins, R.J.E., Loureiro, J.M., Boaventura, R.A.R., (2018), Fish Canning Industry Wastewater Variability Assessment using Multivariate Statistical Methods, Process Safety and Environmental Protection, Volume 102, Pages 263-276. https://doi.Org/10.1016/j.psep.2016.03.016 Domingues, P, Sampaio, P, Arezes, P.M., (2016), Integrated Management Systems Assessment: A Maturity Model Proposal, Journal of Cleaner Production, Volume 124, No. 15, Pages 164-174. https://doi.Org/10.1016/j.jclepro.2016.02.103 Espinosa-Garza, G., Loera-Hernandez, I., Antonyan, N.. (2017), Increase of Productivity through the Study of Work Activities in the Construction Sector, Manufacturing Engineering Society International Conference, 28-30 June, Vigo (Pontevedra)— Spain. Pages 1003-1010. https://doi.Org/10.1016/j.promfg.2017.09.100 Federico, E., (2016), Research in Economics and Industrial Organization, Journal of Research in Economics, Volume 70, No. 4, Pages 511-517. https://doi.Org/10.1016/j. rie.2016.10.002

Fisher, C., (2014), New Techniques in Project Management, American Journal of Industrial and Business Management, Volume 4, No. 12, Pages 739-750. https://doi.org/ 10.4236/ ajibm.2014.412080

Karbasian, M., Rostamkhani, R., (2017), Application of Design of Experiments Technique in Quality Management System for Assessing Various Factors Affecting Processes Performance of Defense Industries Organization, Sharif Journal of Science and Technology, Volume 33.1, No. 1.1, Pages 95-102. https://doi.org/10.24200/J65.2017.5579 Karbasian, M., Rostamkhani. R., (2019), Achieving Productive Reliability through Applying Statistical Distribution Functions, International Journal of Quality and Reliability Management. https://doi.Org/10.l 108/IJQRM-l 1-2018-0298 Karimi Gavareshki, M.H., Abbasi, M., Karbasian, M., Rostamkhani, R., (2018), Application of Quality Engineering Techniques in the Main Domains of Industrial Engineering, Journal of Achievements in Materials & Manufacturing Engineering, Volume 1, No. 90, Pages 22-40. https://doi.org/10.5604/01.3001.0012.7972 Karimi Gavareshki, M.H., Abbasi, M., Karbasian, M., Rostamkhani, R., (2019), Presenting a Productive and Sustainable Model of Integrated Management System for Achieving an

Added Value in Organisational Processes, International Journal of Productivity and Quality Management. https://doi.org/10.1504/IJPQM.2019.10023794

Karirni Gavareshki, M.H., Abbasi, M., Rostamkhani. R., (2017), Application of QFD and VE and Lean Approach for Control Tests in a Product Design, Archives of Materials Science and Engineering, Volume 84, No. 2, Pages 65-78. https://doi.org/ 10.5604/01.3001.0010.0980

Karirni Gavareshki, M.H., Sharifi Zamani, M., Rostamkhani, R., (2014), Identification and Determination of Effective Application of Statistical Prioritize Techniques in Quality Management System in Defense Industries Organization, Iranian Electric Industry Journal of Quality and Productivity, Volume 2, No. 4, Pages 18-29.

Lim, A.H.S., Antony, J., (2016), Statistical Process Control Readiness in the Food Industry: Development of a Self-Assessment Tool, Trends in Food Science and Technology, Volume 58. Pages 133-139.

Lin, S.W., Lee, M., Huang, Y.C., Den, W., (2015), Identifying Water Recycling Strategy using Multivariate Statistical Analysis for High-Tech Industries in Taiwan, Resources Conservation and Recycling, Volume 94, Pages 35-42.

Memon, A.J., Shaikh, M.M., (2016), Confidence Bounds for Energy Conservation in Electric Motors: An Economical Solution using Statistical Techniques, Energy, Volume 109, Pages 592-601. https://doi.Org/10.1016/j.energy.2016.05.014

Montgomery, D., (1996a), Statistical Quality Control (Eighth Edition), translated to Farsi by Noorossana, R., Iran University of Science and Technology, Tehran, Iran.

Montgomery, D., (1996b), Design and Analysis of Experiments (First Edition), translated to Farsi by Noorossana, R., Iran University of Science and Technology, Tehran, Iran.

Nelson, W„ (2004), Accelerated Testing: Statistical Models, Test Plans and Data Analyses, John Wiley & Sons, Hoboken, New Jersey, USA.

Olawumi, T.O., Chan, D.W.M., (2018), A Scientometric Review of Global Research on Sustainability and Sustainable Development, Journal of Cleaner Production, Volume 183, Pages 231-250. https://doi.Org/10.1016/j.jclepro.2018.02.162

Plag, I„ (2006), Encyclopedia of Language & Linguistics (Second Edition), University of Siegen, Siegen, Germany, Pages 121-128.

Porter, A., (2004), Accelerated Testing and Validation, Elsevier, Burlington, MA, USA, Page 01803.

Rajnoha, R., Sujova, A., Dobrovic, J., (2012), Management and Economics of Business Processes Added Value, Procedia, Social and behavioral Sciences, Volume 62, Pages 1292-1296. https://doi.Org/10.1016/j.sbspro.2012.09.221

Rezaei, K., (2001), Using of the Quality Engineering Techniques in the Framework of Quality Management Systems, Second International Quality Management Conference, CQM02 - 002, 22-25 July, Tehran—Iran.

Rezazadeh, S., Jahani, A., Makhdoum, M., Meigooni, H.G., (2017), Evaluation of the Strategic Factors of the Management of Protected Areas using SWOT Analysis, Journal of Ecology, Volume 7. No. 1, Pages 55-68. https://doi.org/10.4236/oje.2017.71005

Salomone, R., (2008), Integrated Management Systems: Experiences in Italian Organizations, Journal of Cleaner Production, Volume 16, No. 16, Pages 1786-1806. https://doi. org/10.1016/j .jclepro.2007.12.003

Sima, H., Jana, P., Panghal, D., (2019), Feasibility of Using Simulation Technique for Line Balancing in Apparel Industry, Procedia Manufacturing, Volume 30, Pages 300-307. https://doi.Org/10.1016/j.promfg.2019.02.043

Tulcidas, A., Nascimento, S., Santos, B., Alvarez, C., Pawlowski, S., Rocha, F., (2019), Statistical Methodology for Scale-up of an Anti-solvent Crystallization Process in the Pharmaceutical Industry, Separation and Purification Technology, Volume 213, Pages 56-62. https://doi.Org/10.1016/j.seppur.2018.12.019

Zhou, X., (2016), Mechanism Design Theory: The Development in Economics and Management, Journal of Business and Management, Volume 4, No. 2, Pages 345-348. https://doi.org/10.4236/ojbm.2016.42036

 
Source
< Prev   CONTENTS   Source   Next >