Bir Gıda Fabrikasında Üretim Planlama Süreçlerinin Analizi ve İyileştirilmesi

Talep tahmini ve üretim planlaması, endüstrideki ana planlama konularıdır. Yetersiz tahmin ve etkisiz üretim planlama prosedürleri, ya fazla stokla ya da karşılanmayan taleple sonuçlanır. Her iki durumda da şirket aşırı kayıplarla karşı karşıyadır. Geçen yüzyılda, bilimsel yönetim ilkeleri oldukça gelişmiştir ve bu sorunları çözmek için kullanılabilir. Ancak, birçok şirket bu konuda ya mühendislik ve yönetim bilgisinden yoksundur ya da halihazırda mevcut olan tahmin ve planlama araçlarını uygulamada dikkatsizdir. Bu çalışma, mevcut yönetim araçlarının kullanımını gösteren ve sadece temel araç ve prosedürleri uygulayarak önemli miktarda maliyet tasarrufunun nasıl sağlanabileceğini gösteren bir vaka uygulaması sunmaktadır. Kağıt, gelecekteki uygulamalarda mühendisler ve üretim planlama yöneticileri için yararlı olabilir.

Analysis and Improvement of Production Planning Processes in a Food Factory

Demand forecasting and production planning are the main planning issues in industry. Poor forecasting and ineffective production planning procedures result in either excess inventories or unmet demand. In either case company faces with excessive losses. Over the past century, scientific management principles have been highly developed and can be used to solve these problems. However, many companies either lack engineering and management knowledge in this respect or are careless in applying already available forecasting and planning tools. This study presents a case application which illustrates the use of available management tools and shows how a significant amount of cost savings can be achieved by just applying basic tools and procedures. The paper can be useful for practicing engineers and production planning managers in future applications.

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  • Amare, T., Singh, B., Kabata, G., and Bhaskaran J. (2021) “Improvement Analysis of Production Planning and Control System”, Idustrial Engineering & Management Vol. 10, No. 3.
  • Jaipuria, S., & Mahapatra, S. S. (2014). An improved demand forecasting method to reduce bullwhip effect in supply chains. Expert Systems with Applications, 41(5), 2395-2408
  • Kandananond, K. (2012). Consumer product demand forecasting based on artificial neural network and support vector machine. International Journal of Economics and Management Engineering, 6(3), 313-316.
  • McGarrie, B. (1998), "Case study: production planning and control ‐ selection, improvement and implementation", Logistics Information Management, Vol. 11 No. 1, pp. 44-52.
  • Mozelewski, T. G., & Scheller, R. M. (2021). Forecasting for intended consequences. Conservation Science and Practice, 3(4), 370-380.
  • Murphy, M. D., O’Mahony, M. J., Shalloo, L., French, P., & Upton, J. (2014). Comparison of modelling techniques for milk- production forecasting. Journal of dairy science, 97(6), 3352-3363.
  • Rianthong, S., Ruekkasaem, L., and Aungkulanon, P. (2019) “Aggregate Production Planning, Case Study in a Small-Sized Company in Thailand”, International Journal of Mechanical Engineering and Technology 10(12): pp.182-187.
  • Savsar, M. and Abdulmalek, F. (2008), “Modeling of a Pull-Push Assembly Control System to Minimize Inventory and Demand Delay Costs”, International Journal of Industrial Engineering, Vol. 15, No. 1.
  • Savsar, M. “Analysis and Improvement of Efficiency for Food Processing Assembly Lines,” International Conference on Production Engineering and Management, 24-25 April 2017, Boston, USA.
  • Shin, S., Ennis, K. L., & Spurlin, W. P. (2015). Effect of inventory management efficiency on profitability: Current evidence from the US manufacturing industry. Journal of Economics and Economic Education Research, 16(1), 98.
  • Wei, Y., Wang, H., & Qi, C. (2013) “On the stability and bullwhip effect of a production and inventory control system”, International Journal of Production Research, 51(1), 154-171.
  • Yenradeea, P., Pinnoi, A., and Charoenthavornying, A. (2001). “Demand Forecasting and Production Planning for Highly Seasonal Demand Situations: Case Study of a Pressure Container Factory”, Science Asia, Vol. 27, pp. 271-278.