Quality Function Deployment for Quality Performance Analysis in Indonesian Automotive Company for Engine Manufacturing

Authors

  • Choesnul Jaqin Master of Industrial Engineering Program, Mercu Buana University, Jakarta
  • Ahmad Rozak Master of Industrial Engineering Program, Mercu Buana University, Jakarta
  • Humiras Hardi Purba Master of Industrial Engineering Program, Mercu Buana University, Jakarta http://orcid.org/0000-0002-8166-6845

DOI:

https://doi.org/10.21512/comtech.v11i1.6164

Keywords:

Quality Function Deployment (QFD), quality performance analysis, automotive company, engine manufacturing, House of Quality (HOQ)

Abstract

The research aimed to improve the quality problem from the previous plant that contributed to the Rate of Quality (RQ) and Overall Equipment Effectiveness (OEE) value in Cylinder Block Machining (CBM). The research was done in one of an automotive company in Indonesia. It had been applying Total Productive Maintenance (TPM) with Kaizen spirit to make continuous improvement even though this company had reached a world-class level on the Japan Institute of Plant Maintenance (JIPM) standard. To express the needs and wants of the current machining plant and improve quality problems from the previous process in the casting plant, the researchers used Quality Function Deployment (QFD) method. From the result, it is known that shrinkage defect at a casting product becomes the priority of the kaizen team to achieve next process customer satisfaction in a machining plant to increase the RQ and OEE value. By implementing improvement based on the highest value of Technical Priorities (TP) from House of Quality (HOQ), it can increase RQ value in CBM from 96,4% in December 2018 to 97,9% in February 2019. Then, OEE value increases from 92% to 93% within two months.

Dimensions

Plum Analytics

References

Al‐Najjar, B. (2001). A concept for detecting quality deviation earlier than when using traditional diagram in automotive: A case study. International Journal of Quality & Reliability Management, 18(9), 917-940. https://doi.org/10.1108/02656710110407118

Azizah, I. N., Lestari, R. N., & Purba, H. H. (2018). Penerapan metode Quality Function Deployment dalam memenuhi kepuasan konsumen pada industri komponen otomotif. Jurnal Teknik Industri, 19(2), 127-136. https://doi.org/10.22219/jtiumm.vol19. no2.127-136

Chowdhury, M. M. H., & Quaddus, M. A. (2016). A multi-phased QFD based optimization approach to sustainable service design. International Journal of Production Economics, 171(January), 165-178. https://doi.org/10.1016/j.ijpe.2015.09.023

Cristiano, J. J., Liker, J. K., & White, C. C. (2000). Customerdriven product development through Quality Function Deployment in the U.S. and Japan. Journal of Product Innovation Management, 17(4), 286-308. https://doi.org/10.1016/S0737-6782(00)00047-3

Darmawan, H., Purba, H. H., Rezeki, R., Hidayat, N., Siregar, A. R., Retna, F., & Aisyah, S. (2017).

Product development strategy with Quality Function Deployment approach: A case study in automotive battery. Management Science Letters, 7(12), 601-610. https://doi.org/10.5267/j.msl.2017.8.005

Fragassa, C., Pavlovic, A., & Massimo, S. (2014). Using a total quality strategy in a new practical approach for improving the product reliability in automotive industry. International Journal for Quality Research, 8(3), 297-310.

Goetsch, D. L., & Davis, S. (2014). Quality management for organizational excellence: Introduction to total quality. Harlow: Pearson.

Hadi, H. A., Purba, H. H., Indarto, K. S., Simarmata, R. G. P., Putra, G. P., Ghazali, D., & Aisyah, S. (2017). The implementation of Quality Function Deployment (QFD) in tire industry. ComTech: Computer, Mathematics and Engineering Applications, 8(4), 223-228. https://doi.org/10.21512/comtech.v8i4.3792

Ionica, A. C., & Leba, M. (2015). QFD integrated in new product development - Biometric identification system case study. Procedia Economics and Finance, 23, 986-991. https://doi.org/10.1016/s2212-5671(15)00454-2

Jin, J., Ji, P., Liu, Y., & Johnson Lim, S. C. (2015). Translating online customer opinions into engineering characteristics in QFD: A probabilistic language analysis approach. Engineering Applications of Artificial Intelligence, 41(May), 115-127. https://doi.org/10.1016/j.engappai.2015.02.006

Kermanpur, A., Mahmoudi, S., & Hajipour, A. (2008). Numerical simulation of metal flow and solidification in the multi-cavity casting moulds of automotive components. Journal of Materials Processing Technology, 206(1-3), 62-68. https://doi.org/10.1016/j.jmatprotec.2007.12.004

Kusuma, F. A., & Sharif, O. O. (2019). Analisis customer value index dalam memilih mobil hatchback di Indonesia. E-Proceeding of Management, 6(3), 5498-5509.

Ko, W. C. (2015). Construction of house of quality for new product planning: A 2-tuple fuzzy linguistic approach. Computers in Industry, 73(October), 117-127. https://doi.org/10.1016/j.compind.2015.07.008

Moghimi, V., Jusan, M. B. M., Izadpanahi, P., & Mahdinejad, J. (2017). Incorporating user values into housing design through indirect user participation using MEC-QFD model. Journal of Building Engineering, 9(January), 76-83. https://doi.org/10.1016/j.jobe.2016.11.012

Nurcahyo, R., & Wibowo, A. D. (2015). Manufacturing capability, manufacturing strategy and performance of Indonesia automotive component manufacturer. Procedia CIRP, 26, 653-657. https://doi.org/10.1016/j.procir.2014.07.046

Pawestri, V., Setiawan, A., & Linawati, L. (2019). Pemodelan data penjualan mobil menggunakan model autoregressive moving average berdasarkan metode bayesian. Jurnal Sains dan Edukasi Sains, 2(1), 26-35. https://doi.org/10.24246/juses.v2i1p26-35

Punnakitikashem, P., Laosirihongthong, T., Adebanjo, D., & McLean, M. W. (2010). A study of quality management practices in TQM and non-TQM firms: Findings from the ASEAN automotive industry. International Journal of Quality & Reliability Management, 27(9), 1021-1035. https://doi.org/10.1108/02656711011084819

Purba, H. H., Prayogo, H., Wibowo, R., Pradipta, Y., & Aisyah, S. (2017). Increasing the thermal comfort, ergonomics and safety of helmet by using of Quality Function Deployment method: A case study in Indonesia. Journal of Scientific and Engineering Research, 4(7), 184-192.

Rizlan, W., Purba, H. H., & Sudiyono. (2018). Performance maintenance analysis using QFD method: A case study in fabrication company in Indonesia. ComTech: Computer, Mathematics and Engineering Applications, 9(1), 25-35. https://doi.org/10.21512/comtech.v9i1.4456

Romli, I., Pusnawati, E., & Siswandi, A. (2019). Penentuan tingkat penjualan mobil di Indonesia dengan menggunakan Algoritma Naive Bayes. E-Prosiding SNasTekS 2019, 1(1), 367-380.

Rosso, M., & Grande, M. A. (2007). Influence of the casting process on the properties of AI based automotive components. In Advanced Materials Research (Vol. 23, pp. 25-32). Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMR.23.25

Rozak, A., Shadrina, A., & Rimawan, E. (2019). Kaizenin world class automotive company with reduction of six big lossesin cylinder block machining line in Indonesia. International Journal of Innovative Science and Research Technology, 4(7), 339-344.

Schillo, R. S., Isabelle, D. A., & Shakiba, A. (2017). Linking advanced biofuels policies with stakeholder interests: A method building on Quality Function Deployment. Energy Policy, 100(January), 126-137. https://doi.org/10.1016/j.enpol.2016.09.056

Stylidis, K., Wickman, C., & Söderberg, R. (2015). Defining perceived quality in the automotive industry: An engineering approach. Procedia CIRP, 36, 165-170. https://doi.org/10.1016/j.procir.2015.01.076

Yadav, O. P., & Goel, P. S. (2008). Customer satisfaction driven quality improvement target planning for product development in automotive industry. International Journal of Production Economics, 113(2), 997-1011. https://doi.org/10.1016/j.ijpe.2007.12.008

Downloads

Published

2020-06-30

Issue

Section

Articles
Abstract 1543  .
PDF downloaded 802  .