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COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY

Year 2018, Volume: 13 Issue: 4, 324 - 333, 13.10.2018

Abstract

There is an increasing competition between companies for their survival
in today’s business environment. Not only time but also cost parameters affect
the company’s sustainability performance. Logistics as one of the core
operations of companies has a large share on expenses. Transport, warehousing,
administration, packaging, and other indirect costs constitute the main cost
values of logistics. Especially product damages caused by incorrect packing and
transportation leads to extra expenditures to the companies and damages their
reputation due to the customer dissatisfaction. In order to avoid such
situations, proper level of packaging for protection, transportation
conditions, features of the product like fragility, compactness, must be
selected and matched correctly. On the other hand, some external factors such
as temperature and humidity, which affect the quality of cardboard, also need
to be considered in the production phase. In this study, a Design of Experiment
methodology is performed to determine the suitable conditions for increasing
the strength of the corrugated cardboard box that is used by a Glassware
Company operating in Turkey. 3k full factorial design approach is
implemented for the analysis and box compression test is used for measurement. The
discussed factors and the interactions of the factors were evaluated with the
help of Minitab software.

References

  • [1] Layer, A., Brinke, E.T., Houten, F.V., Kals, H., and Haasis, S., (2002). Recent and Future Trends in Cost Estimation. International Journal of Computer Integrated Manufacturing, 15(6), 499-510.
  • [2] Kuhn, H. and Sternbeck, M.G., (2013). Integrative Retail Logistics: An Exploratory Study. Operations Management Research, 6(1-2), 2-18.
  • [3] Siepermann, C., (2007). Logistics Cost Accounting: Which System is Best Suited?. In Proceedings of the 12th International Symposium on Logistics (K.S. Pawar, C.S. Lalwani, M. Muffatto. ed.), Nottingham University Business School, Nottingham (pp:70-278).
  • [4] Engblom, J., Solakivi, T., Töyli, J., and Ojala, L., (2012). Multiple-Method Analysis of Logistics Costs. International Journal of Production Economics, 137(1), 29-35.
  • [5] Zeng, A.Z. and Rossetti, C., (2003). Developing a Framework for Evaluating the Logistics Costs in Global Sourcing Processes: An Implementation and Insights. International Journal of Physical Distribution & Logistics Management, 33(9), 785-803.
  • [6] Weiyi, F. and Luming, Y., (2009). The Discussion of Target Cost Method in Logistics Cost Management. ISECS International Colloquium on Computing, Communication, Control, and Management, 537-540.
  • [7] Havenga, J., (2010). Logistics Costs in South Africa–The Case for Macroeconomic Measurement. South African Journal of Economics, 78(4), 460-476.
  • [8] Silva, T.F., Gonçalves, A.T., and Leite, M.S., (2014). Logistics Cost Management: Insights on Tools and Operations. International Journal of Logistics Systems and Management, 19(3), 329-346.
  • [9] Churchill, G.A., (2002). Fundamentals of Experimental Design for cDNA Microarrays. Nature Genetics, 490–495.
  • [10] Turley, L.W. and Milliman, R.E., (2000). Atmospheric Effects on Shopping Behavior: A Review of The Experimental Evidence. Journal of Business Research, 49(2), 193-211.
  • [11] Wahdame, B., Candusso, D., François, X., Harel, F., Kauffmann, J.M., and Coquery, G., (2009). Design of Experiment Techniques for Fuel Cell Characterisation and Development. International Journal of Hydrogen Energy, 34(2), 967-980.
  • [12] Shang, J.S., Li, S., and Tadikamalla, P., (2004). Operational Design of a Supply Chain System Using the Taguchi Method, Response Surface Methodology, Simulation, and Optimization. International Journal of Production Research, 42(18), 3823-3849.
  • [13] Biehl, M., Prater, E., and Realff, M.J., (2005). Assessing Performance and Uncertainty in Developing Carpet Reverse Logistics Systems. Computers & Operations Research, 34(2), 443-463.
  • [14] Manzini, R., Gamberi, M., Persona, A., and Regattieri, A., (2007). Design of a Class Based Storage Picker to Product Order Picking System. International Journal of Advance Manufacturing Technology, 32(7-8), 811–821.
  • [15] Curcio, D. and Longo, F., (2009). Inventory and Internal Logistics Management as Critical Factors Affecting the Supply Chain Performances. International Journal of Simulation and Process Modelling, 5(4), 278-288.
  • [16] Hussain, M., Drake, P. R., & Myung Lee, D., (2012). Quantifying the Impact of a Supply Chain's Design Parameters on the Bullwhip Effect Using Simulation and Taguchi Design of Experiments. International Journal of Physical Distribution & Logistics Management, 42(10), 947-968.
  • [17] Cannella, S., Bruccoleri, M., and Framinan, J.M., (2016). Closed-Loop Supply Chains: What Reverse Logistics Factors Influence Performance?. International Journal of Production Economics, 175, 35-49.
  • [18] Chackelson, C., Errasti, A., Ciprés, D., and Lahoz, F., (2013). Evaluating Order Picking Performance Trade-Offs by Configuring Main Operating Strategies in a Retail Distributor: A Design of Experiments Approach. International Journal of Production Research, 51(20), 6097-6109.
  • [19] Van Hung, D., Nakano, Y., Tanaka, F., Hamanaka, D., and Uchino, T., (2010). Preserving the Strength of Corrugated Cardboard Under High Humidity Condition Using Nano-Sized Mists. Composites Science and Technology, 70(14), 2123-2127.
  • [20] Carstens, R., (1992). U.S. Patent No. 5,085,367. Washington, DC: U.S. Patent and Trademark Office.
  • [21] Büyüksaatçı, S., (2015). Bat Algorithm Application for the Single Row Facility Layout Problem. In Recent Advances in Swarm Intelligence and Evolutionary Computation (pp:101-120). Springer, Cham.
  • [22] Montgomery, D.C., (2013). Design and Analysis of Experiments, 8th Edition. JohnWiley & Sons.

COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY

Year 2018, Volume: 13 Issue: 4, 324 - 333, 13.10.2018

Abstract

There is an increasing competition between companies for their survival in today’s business environment. Not only time but also cost parameters affect the company’s sustainability performance. Logistics as one of the core operations of companies has a large share on expenses. Transport, warehousing, administration, packaging, and other indirect costs constitute the main cost values of logistics. Especially product damages caused by incorrect packing and transportation leads to extra expenditures to the companies and damages their reputation due to the customer dissatisfaction. In order to avoid such situations, proper level of packaging for protection, transportation conditions, features of the product like fragility, compactness, must be selected and matched correctly. On the other hand, some external factors such as temperature and humidity, which affect the quality of cardboard, also need to be considered in the production phase. In this study, a Design of Experiment methodology is performed to determine the suitable conditions for increasing the strength of the corrugated cardboard box that is used by a Glassware Company operating in Turkey. 3k full factorial design approach is implemented for the analysis and box compression test is used for measurement. The discussed factors and the interactions of the factors were evaluated with the help of Minitab software.

References

  • [1] Layer, A., Brinke, E.T., Houten, F.V., Kals, H., and Haasis, S., (2002). Recent and Future Trends in Cost Estimation. International Journal of Computer Integrated Manufacturing, 15(6), 499-510.
  • [2] Kuhn, H. and Sternbeck, M.G., (2013). Integrative Retail Logistics: An Exploratory Study. Operations Management Research, 6(1-2), 2-18.
  • [3] Siepermann, C., (2007). Logistics Cost Accounting: Which System is Best Suited?. In Proceedings of the 12th International Symposium on Logistics (K.S. Pawar, C.S. Lalwani, M. Muffatto. ed.), Nottingham University Business School, Nottingham (pp:70-278).
  • [4] Engblom, J., Solakivi, T., Töyli, J., and Ojala, L., (2012). Multiple-Method Analysis of Logistics Costs. International Journal of Production Economics, 137(1), 29-35.
  • [5] Zeng, A.Z. and Rossetti, C., (2003). Developing a Framework for Evaluating the Logistics Costs in Global Sourcing Processes: An Implementation and Insights. International Journal of Physical Distribution & Logistics Management, 33(9), 785-803.
  • [6] Weiyi, F. and Luming, Y., (2009). The Discussion of Target Cost Method in Logistics Cost Management. ISECS International Colloquium on Computing, Communication, Control, and Management, 537-540.
  • [7] Havenga, J., (2010). Logistics Costs in South Africa–The Case for Macroeconomic Measurement. South African Journal of Economics, 78(4), 460-476.
  • [8] Silva, T.F., Gonçalves, A.T., and Leite, M.S., (2014). Logistics Cost Management: Insights on Tools and Operations. International Journal of Logistics Systems and Management, 19(3), 329-346.
  • [9] Churchill, G.A., (2002). Fundamentals of Experimental Design for cDNA Microarrays. Nature Genetics, 490–495.
  • [10] Turley, L.W. and Milliman, R.E., (2000). Atmospheric Effects on Shopping Behavior: A Review of The Experimental Evidence. Journal of Business Research, 49(2), 193-211.
  • [11] Wahdame, B., Candusso, D., François, X., Harel, F., Kauffmann, J.M., and Coquery, G., (2009). Design of Experiment Techniques for Fuel Cell Characterisation and Development. International Journal of Hydrogen Energy, 34(2), 967-980.
  • [12] Shang, J.S., Li, S., and Tadikamalla, P., (2004). Operational Design of a Supply Chain System Using the Taguchi Method, Response Surface Methodology, Simulation, and Optimization. International Journal of Production Research, 42(18), 3823-3849.
  • [13] Biehl, M., Prater, E., and Realff, M.J., (2005). Assessing Performance and Uncertainty in Developing Carpet Reverse Logistics Systems. Computers & Operations Research, 34(2), 443-463.
  • [14] Manzini, R., Gamberi, M., Persona, A., and Regattieri, A., (2007). Design of a Class Based Storage Picker to Product Order Picking System. International Journal of Advance Manufacturing Technology, 32(7-8), 811–821.
  • [15] Curcio, D. and Longo, F., (2009). Inventory and Internal Logistics Management as Critical Factors Affecting the Supply Chain Performances. International Journal of Simulation and Process Modelling, 5(4), 278-288.
  • [16] Hussain, M., Drake, P. R., & Myung Lee, D., (2012). Quantifying the Impact of a Supply Chain's Design Parameters on the Bullwhip Effect Using Simulation and Taguchi Design of Experiments. International Journal of Physical Distribution & Logistics Management, 42(10), 947-968.
  • [17] Cannella, S., Bruccoleri, M., and Framinan, J.M., (2016). Closed-Loop Supply Chains: What Reverse Logistics Factors Influence Performance?. International Journal of Production Economics, 175, 35-49.
  • [18] Chackelson, C., Errasti, A., Ciprés, D., and Lahoz, F., (2013). Evaluating Order Picking Performance Trade-Offs by Configuring Main Operating Strategies in a Retail Distributor: A Design of Experiments Approach. International Journal of Production Research, 51(20), 6097-6109.
  • [19] Van Hung, D., Nakano, Y., Tanaka, F., Hamanaka, D., and Uchino, T., (2010). Preserving the Strength of Corrugated Cardboard Under High Humidity Condition Using Nano-Sized Mists. Composites Science and Technology, 70(14), 2123-2127.
  • [20] Carstens, R., (1992). U.S. Patent No. 5,085,367. Washington, DC: U.S. Patent and Trademark Office.
  • [21] Büyüksaatçı, S., (2015). Bat Algorithm Application for the Single Row Facility Layout Problem. In Recent Advances in Swarm Intelligence and Evolutionary Computation (pp:101-120). Springer, Cham.
  • [22] Montgomery, D.C., (2013). Design and Analysis of Experiments, 8th Edition. JohnWiley & Sons.
There are 22 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Sinem Buyuksaatcı Kırıs 0000-0001-7697-3018

Mesut Samastı This is me 0000-0002-4900-8279

Ş. Alp Baray 0000-0002-5468-225X

Publication Date October 13, 2018
Published in Issue Year 2018 Volume: 13 Issue: 4

Cite

APA Buyuksaatcı Kırıs, S., Samastı, M., & Baray, Ş. A. (2018). COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY. Engineering Sciences, 13(4), 324-333.
AMA Buyuksaatcı Kırıs S, Samastı M, Baray ŞA. COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY. Engineering Sciences. October 2018;13(4):324-333.
Chicago Buyuksaatcı Kırıs, Sinem, Mesut Samastı, and Ş. Alp Baray. “COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY”. Engineering Sciences 13, no. 4 (October 2018): 324-33.
EndNote Buyuksaatcı Kırıs S, Samastı M, Baray ŞA (October 1, 2018) COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY. Engineering Sciences 13 4 324–333.
IEEE S. Buyuksaatcı Kırıs, M. Samastı, and Ş. A. Baray, “COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY”, Engineering Sciences, vol. 13, no. 4, pp. 324–333, 2018.
ISNAD Buyuksaatcı Kırıs, Sinem et al. “COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY”. Engineering Sciences 13/4 (October 2018), 324-333.
JAMA Buyuksaatcı Kırıs S, Samastı M, Baray ŞA. COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY. Engineering Sciences. 2018;13:324–333.
MLA Buyuksaatcı Kırıs, Sinem et al. “COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY”. Engineering Sciences, vol. 13, no. 4, 2018, pp. 324-33.
Vancouver Buyuksaatcı Kırıs S, Samastı M, Baray ŞA. COST AND QUALITY FOCUSED SUITABLE BOX DETERMINATION WITH DESIGN OF EXPERIMENT: A CASE OF A GLASSWARE COMPANY. Engineering Sciences. 2018;13(4):324-33.