MOLDS PRODUCTION PROGRESS MAPPING – A VISUAL MANAGEMENT TOOL FOR THE INDUSTRY 4.0

Authors

  • Diogo Pina Jorge Erising, Cascais, Portugal
  • Paulo Peças IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

DOI:

https://doi.org/10.32358/rpd.2018.v4.312

Keywords:

molds production, production planning, process mapping, visual management, industry 4.0

Abstract

The planning of injection molds production is a complex task where the classic planning approaches has proven limitations because of the following particular characteristics: the mold expands in a myriad of components for production; the “one-of-a-kind” type of production and recurrent mold design changes asked by the customer. To overcome this challenge a methodology to Molds Production progress Mapping is proposed (MPM). The methodology was built on the authors experience in collaborating with mold making companies, on the principles of lean manufacturing and visual management (VM) and also have in mind the trend towards production digitalization to be aligned with Industry 4.0 evolution. As a VM tool to support molds production planning, the MPM shows the instant progress of each mold, the deviation from planning and the remaining time for the due date.  The user has “only” to input the mold’s components critic level and the relative weight of each production process in the total time; it also requires that the production process are armed with sensors and the production task are digitalized and compiled in the information management system. The MPM can also be used in other complex production systems.

Downloads

Download data is not yet available.

References

APOSTU, M.V., BENDUL, J. Long-term capacity planning in die manufacturing using the estimated product cost: an exploratory research. 48th CIRP Conference on MANUFACTURING SYSTEMS – CIRP CMC 2015, Ischia (Nápoles), Italia, 2015.

DUJIN, A., GEISSLER,C., HORSTKOTTERR, D. INDUSTRY 4.0, The new industrial revolution - How Europe will succeed. Think-Act, Roland Berger SC, 2014.

FLORJANIČ, B., KUZMAN, K. Estimation of Time for Manufacturing of Injection Moulds Using Artificial Neural Networks-based Model, POLIMERI, 33:1, 12-21, 2012.

GALSWORTH, G. D., Visual Workplace - Visual Thinking, Visual-Lean Enterprise Press, 2013.

HENRIQUES, E., PEÇAS, P., CUNHA, P. Perspectives of Mould Making Industry for Global Digital Manufacturing. Digital Enterprise Technologies – Perspectives and Future Challenges, P. Cunha, F. Maropoulos (Eds.), Springer, p. 449-456, 2007.

HENRIQUES, E., PEÇAS, P. The Need for Agile Manufacturing Implementation in Mould Making Business. Business Excellence, 2003.

HENRIQUES, E. PEÇAS, P. Organizational and Manufacturing Best-Practices to Improve Mould Making Competitiveness. RPD, 2004.

HENRIQUES, E., PEÇAS, P. New Business Models for the Tooling Industry. Advances in Business and Management, ed. Nelson, W.D., Nova Science Publishers, New York, 2012.

IMAI, M. Gemba Kaizen, McGraw-Hill, 1997.

PLASTICSEUROPE, Plastics - the Facts 2015 - An analysis of European plastics production, demand and waste data, 2015.

ROTHER, M., SHOOK, J. Learning to See: Value Stream Mapping to Add Value and Eliminate Muda. The Lean Enterprise Institute, Inc., 2009.

WEF, The World Economic Forum. The New Plastics Economy: Rethinking the future of plastics, 2016.

WOMACK, J.P., JONES, D.T., ROSS, D. The machine that changed the world, New York: Macmillan Publishing Company, 1990.

WONGWIWAT, Asawin; BOHEZ, Erik LJ; PISUCHPEN, Roongrat. Production scheduling for injection molding manufacture using Petri Net model. Assembly Automation, v. 33, n. 3, p. 282-293, 2013.

WRYE, M. Visual Management is Critical to Lean, Beyond Lean, 2016 [Online]. Available: https://beyondlean.wordpress.com. [Acedido em 2017 04 13].

ZAWILA, J. Avoid bad planning. Moldmaking Technology Magazine, 1/1/2002, 2002.

Published

2018-03-30

How to Cite

Jorge, D. P., & Peças, P. (2018). MOLDS PRODUCTION PROGRESS MAPPING – A VISUAL MANAGEMENT TOOL FOR THE INDUSTRY 4.0. Revista Produção E Desenvolvimento, 4(1), 68–81. https://doi.org/10.32358/rpd.2018.v4.312

Issue

Section

Dossier "Energy and climate"