Análise das principais métricas utilizadas por profissionais na avaliação da maturidade de projetos de lean

Vivien Cielusinsky, Rosley Anholon, Izabela Simon Rampasso, Dirceu Silva, Osvaldo L. G. Quelhas

Resumo


O Lean Manufacturing é uma estratégia de produção aplicada em empresas de diversos segmentos. Seu principal objetivo é reduzir ao máximo os desperdícios a fim de maximizar o lucro. A transição para o referido estágio, entretanto, não é simples e muitas são as barreiras enfrentadas para se alcançar os objetivos supracitados. Nesta trajetória, as empresas apresentarão diferentes estágios de maturidade e a mensuração desta maturidade torna-se importante. Tomando por base as informações mencionadas, o presente artigo tem por objetivo identificar quais são as principais métricas utilizadas por empresas brasileiras na avaliação da maturidade de sistemas lean. Métricas utilizadas em projetos lean foram listadas a partir da literatura e informações sobre a aplicação das mesmas foram levantadas junto a 43 profissionais que participaram de uma survey. Respondentes outliers foram identificados a partir do Escalonamento Multidimensional (EMD) e, na sequência, as métricas foram ordenadas via um mecanismo utilizado pelo software SPSS para combinação linear de variáveis, empregado na Análise Fatorial Exploratória. Os resultados evidenciaram que as métricas mais aplicadas estão relacionadas à produtividade dos funcionários, número de reclamações dos consumidores, tempo de setup, lead times e índice de estoques. Os resultados decorrentes deste estudo poderão ser utilizados por outros pesquisadores em suas futuras pesquisas.


Palavras-chave


Gestão da Produção. Lean Manufacturing. Métricas para avaliação da maturidade.

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Referências


AGARWAL, A.; SHANKAR, R.; TIWARI, M. K. Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach. European Journal of Operational Research, v. 173, n. 1, p. 211–225, 2006. https://doi.org/10.1016/j.ejor.2004.12.005

ANHOLON, R.; SANO, A. T. Analysis of critical processes in the implementation of lean manufacturing projects using project management guidelines. The International Journal of Advanced Manufacturing Technology, v. 84, n. 9–12, p. 2247–2256, 2016. https://doi.org/10.1007/s00170-015-7865-9

ANVARI, A.; ZULKIFLI, N.; YUSUFF, R. M. A dynamic modeling to measure lean performance within lean attributes. The International Journal of Advanced Manufacturing Technology, v. 66, n. 5–8, p. 663–677, 2013. https://doi.org/10.1007/s00170-012-4356-0

ARUNAGIRI, P.; GNANAVELBABU, A. Identification of high impact lean production tools in automobile industries using weighted average method. Procedia Engineering, v. 97, p. 2072–2080, 2014. https://doi.org/10.1016/j.proeng.2014.12.450

BABALOLA, O.; IBEM, E. O.; EZEMA, I. C. Implementation of lean practices in the construction industry: A systematic review. Building and Environment, v. 148, n. October 2018, p. 34–43, 2018. https://doi.org/10.1016/j.buildenv.2018.10.051

BEHROUZI, F.; WONG, K. Y. An integrated stochastic-fuzzy modeling approach for supply chain leanness evaluation. International Journal of Advanced Manufacturing Technology, v. 68, n. 5–8, p. 1677–1696, 2013. https://doi.org/10.1007/s00170-013-4966-1

BHASIN, S. Measuring the Leanness of an organisation. International Journal of Lean Six Sigma, v. 2, n. 1, p. 55–74, 2011. https://doi.org/10.1108/20401461111119459

BHASIN, S. Prominent obstacles to lean. International Journal of Productivity and Performance Management, v. 61, n. 4, p. 403–425, 2012. https://doi.org/10.1108/17410401211212661

BORG, I.; GROENEN, P. Modern Multidimensional Scaling. New York, NY: Springer New York, 1997. https://doi.org/10.1007/978-1-4757-2711-1

BÜYÜKÖZKAN, G.; KAYAKUTLU, G.; KARAKADILAR, İ. S. Assessment of Lean Manufacturing Effect on Business Performance using Bayesian Belief Networks. Expert Systems with Applications, v. 42, n. 19, p. 6539–6551, 2015. https://doi.org/10.1016/j.eswa.2015.04.016

CAZERI, G. T. et al. An assessment of the integration between corporate social responsibility practices and management systems in Brazil aiming at sustainability in enterprises. Journal of Cleaner Production, 2018. https://doi.org/10.1016/j.jclepro.2018.02.023

CHAUHAN, G.; SINGH, T. P. Measuring parameters of lean manufacturing realization. Measuring Business Excellence, v. 16, n. 3, p. 57–71, 2012. https://doi.org/10.1108/13683041211257411

CORIAT, B. Pensar pelo avesso: o modelo japonês de trabalho e organização. Rio de Janeiro: UFRJ/ Revan, 1994.

DEIF, A. M.; ELMARAGHY, H. Cost performance dynamics in lean production leveling. Journal of Manufacturing Systems, v. 33, n. 4, p. 613–623, out. 2014. https://doi.org/10.1016/j.jmsy.2014.05.010

FÁVERO, L. P. et al. Análise de dados: modelagem multivariada para tomada de decisões. [s.l.] Campus, 2009.

FIELD, A. Discovering Statistics Using SPSS. 3. ed. London: Sage Publications, 2009.

FORNO, A. J. D. et al. Value stream mapping: A study about the problems and challenges found in the literature from the past 15 years about application of Lean tools. International Journal of Advanced Manufacturing Technology, v. 72, n. 5–8, p. 779–790, 2014. https://doi.org/10.1007/s00170-014-5712-z

GELEI, A.; LOSONCI, D.; MATYUSZ, Z. Lean production and leadership attributes - the case of Hungarian production managers. Journal of Manufacturing Technology Management, v. 26, n. 4, p. 477–500, 2015. https://doi.org/10.1108/JMTM-05-2013-0059

GHOSH, M. Lean manufacturing performance in Indian manufacturing plants. Journal of Manufacturing Technology Management, v. 24, n. 1, p. 113–122, 2012. https://doi.org/10.1108/17410381311287517

GIL, A. Como Elaborar Projetos de Pesquisa. São Paulo: Editora Atlas, 2010.

HAIR, J. F. et al. Multivariate Data Analysis. 7. ed. [s.l.] Pearson, 2009.

JABBOUR, A. B. L. D. S.; JUNIOR, J. C. O.; JABBOUR, C. J. C. Extending lean manufacturing in supply chains: A successful case in brazil. Benchmarking: An International Journal, v. 21, n. 6, p. 1070–1083, 2014. https://doi.org/10.1108/BIJ-01-2013-0014

JADHAV, J. R.; MANTHA, S. S.; RANE, S. B. Exploring barriers in lean implementation. International Journal of Lean Six Sigma, v. 5, n. 2, p. 122–148, 2014. https://doi.org/10.1108/IJLSS-12-2012-0014

JING, S.; NIU, Z.; CHANG, P.-C. The application of VIKOR for the tool selection in lean management. Journal of Intelligent Manufacturing, p. 1–15, 14 set. 2015.

KARIM, A.; ARIF‐UZ‐ZAMAN, K. A methodology for effective implementation of lean strategies and its performance evaluation in manufacturing organizations. Business Process Management Journal, v. 19, n. 1, p. 169–196, 2013. https://doi.org/10.1108/14637151311294912

KEYSER, R. S.; SAWHNEY, R. S. Reliability in lean systems. International Journal of Quality & Reliability Management, v. 30, n. 3, p. 223–238, 2013. https://doi.org/10.1108/02656711311299818

KHANCHANAPONG, T. et al. The unique and complementary effects of manufacturing technologies and lean practices on manufacturing operational performance. International Journal of Production Economics, v. 153, p. 191–203, 2014. https://doi.org/10.1016/j.ijpe.2014.02.021

LACERDA, A. P.; XAMBRE, A. R.; ALVELOS, H. M. Applying Value Stream Mapping to eliminate waste: A case study of an original equipment manufacturer for the automotive industry. International Journal of Production Research, v. 54, n. 6, p. 1708–1720, 2016. https://doi.org/10.1080/00207543.2015.1055349

LEYER, M.; MOORMANN, J. How lean are financial service companies really? Empirical evidence from a large scale study in Germany. International Journal of Operations and Production Management, v. 34, n. 11, p. 1366–1388, 2014. https://doi.org/10.1108/IJOPM-06-2013-0296

LIN, L.; FONG, D. K. H. Bayesian multidimensional scaling procedure with variable selection. Computational Statistics and Data Analysis, v. 129, p. 1–13, 2019. https://doi.org/10.1016/j.csda.2018.07.007

LOSONCI, D.; DEMETER, K. Lean production and business performance: international empirical results. Competitiveness Review: An International Business Journal incorporating Journal of Global Competitiveness, v. 23, n. 3, p. 218–233, 2013. https://doi.org/10.1108/10595421311319816

LUCATO, W. C. et al. Performance evaluation of lean manufacturing implementation in Brazil. International Journal of Productivity and Performance Management, v. 63, n. 5, p. 529–549, 2014. https://doi.org/10.1108/IJPPM-04-2013-0085

MARODIN, G. et al. Lean product development and lean manufacturing: Testing moderation effects. International Journal of Production Economics, v. 203, n. March, p. 301–310, 2018. https://doi.org/10.1016/j.ijpe.2018.07.009

MESSAGE COSTA, L. B. et al. Lean, six sigma and lean six sigma in the food industry: A systematic literature review. Trends in Food Science & Technology, v. 82, n. August, p. 122–133, 2018. https://doi.org/10.1016/j.tifs.2018.10.002

OHNO, T. O Sistema Toyota de Produção: além da produção em larga escala. Porto Alegre: Bookman, 1997.

PAMPANELLI, A. B.; FOUND, P.; BERNARDES, A. M. A Lean & Green Model for a production cell. Journal of Cleaner Production, v. 85, p. 19–30, 2014. https://doi.org/10.1016/j.jclepro.2013.06.014

RAMPASSO, I. S.; ANHOLON, R. Parâmetros para avaliação de células de manufatura que utilizam a filosofia lean: uma revisão da literatura. Revista Produção Online, v. 17, n. 4, p. 1329, 15 dez. 2017. https://doi.org/10.14488/1676-1901.v17i4.2637

ROTHER, M.; SHOOK, J. Aprendendo a enxergar: mapeando o fluxo de valor para agregar valor e eliminar o desperdício. São Paulo: Lean Institute Brasil, 2012.

SIBSON, R. Studies in the Robustness of Multidimensional Scaling: Perturbational Analysis of Classical Scaling. Journal of the Royal Statistical Society. Series B (Methodological), v. 41, n. 2, p. 217–229, 1979. https://doi.org/10.1111/j.2517-6161.1979.tb01076.x

SILVA, E. L.; MENEZES, E. M. Metodologia da Pesquisa e Elaboração de Dissertação - 4a edição. Portal, p. 138p, 2005.

SILVA, S. K. P. N.; PERERA, H. S. C.; SAMARASINGHE, G. D. Viability of Lean Manufacturing Tools and Techniques in the Apparel Industry in Sri Lanka. Applied Mechanics and Materials, v. 110–116, p. 4013–4022, 2012. https://doi.org/10.4028/www.scientific.net/AMM.110-116.4013

SRINIVASARAGHAVAN, J.; ALLADA, V. Application of mahalanobis distance as a lean assessment metric. International Journal of Advanced Manufacturing Technology, v. 29, n. 11–12, p. 1159–1168, 2006. https://doi.org/10.1007/s00170-005-0004-2

UFUA, D. E.; PAPADOPOULOS, T.; MIDGLEY, G. Systemic Lean Intervention: Enhancing Lean with Community Operational Research. European Journal of Operational Research, v. 268, n. 3, p. 1134–1148, 2018. https://doi.org/10.1016/j.ejor.2017.08.004

UGOCHUKWU, P.; ENGSTROM, J.; LANGSTRAND, J. Lean In The Supply Chain: A Literature Review. Management and Production Engineering Review, v. 3, n. 4, p. 87–96, 2013.

WAN, H. DA; FRANK CHEN, F. A leanness measure of manufacturing systems for quantifying impacts of lean initiatives. International Journal of Production Research, v. 46, n. 23, p. 6567–6584, 2008. https://doi.org/10.1080/00207540802230058

WOMACK, J. P.; JONES, D. T. A mentalidade enxuta nas empresas: elimine o desperdício e crie riqueza. Rio de Janeiro: Campus, 1998.

ZHOU, B. Lean principles, practices, and impacts: a study on small and medium-sized enterprises (SMEs). Annals of Operations Research, v. 241, n. 1–2, p. 457–474, 6 jun. 2016. https://doi.org/10.1007/s10479-012-1177-3




DOI: https://doi.org/10.14488/1676-1901.v20i1.3470

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