2011International Journal of Production ResearchRequires access

An improved production planning method for process industries

Pingfa Feng, Jianfu Zhang, Zhijun Wu, Dingwen Yu

Open publisher page 26 citations

Abstract

An effective production planning method plays a key role in the production management system for the process manufacturing industries. It is particularly important to develop ways to solve the problems under demand uncertainty, planning inadequacy and capability unbalance. In this article, we present a process industries oriented production planning optimisation method that focuses on minimising inventory costs, and optimising production load rate and balance load rate. By analysing the demand forecasts model and minimum inventory costs control model, we propose how to achieve total production demand amounts in correlation with production orders. We also discuss the Weibull distribution-obeyed equipment repair model to maximise the equipment utilisation rate. The equipment repair time is also considered when specifying the production lead time. The production planning system optimisation objectives function is given, in the condition of the equipment production capacity model and the smallest economic batch requirement. To validate the proposed methods, real production and sales data are sampled from a pharmaceutical plant. The case study shows that the improved production planning models are more targeted and effective for Chinese process industries.

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What this paper is about

An effective production planning method plays a key role in the production management system for the process manufacturing industries. It is particularly important to develop ways to solve the problems under demand uncertainty, planning inadequacy and capability unbalance. In this article, we present a process industries oriented production planning optimisation method that focuses on minimising inventory costs, and optimising production load rate and balance load rate. By analysing the demand forecasts model and minimum inventory costs control model, we propose how to achieve total production demand amounts in correlation with production orders. We also discuss the Weibull distribution-obeyed equipment repair model to maximise the equipment utilisation rate. The equipment repair time is also considered when specifying the production lead time. The production planning system optimisation objectives function is given, in the condition of the equipment production capacity model and the smallest economic batch requirement. To validate the proposed methods, real production and sales data are sampled from a pharmaceutical plant. The case study shows that the improved production planning models are more targeted and effective for Chinese process industries.

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Available abstract

An effective production planning method plays a key role in the production management system for the process manufacturing industries. It is particularly important to develop ways to solve the problems under demand uncertainty, planning inadequacy and capability unbalance. In this article, we present a process industries oriented production planning optimisation method that focuses on minimising inventory costs, and optimising production load rate and balance load rate. By analysing the demand forecasts model and minimum inventory costs control model, we propose how to achieve total production demand amounts in correlation with production orders. We also discuss the Weibull distribution-obeyed equipment repair model to maximise the equipment utilisation rate. The equipment repair time is also considered when specifying the production lead time. The production planning system optimisation objectives function is given, in the condition of the equipment production capacity model and the smallest economic batch requirement. To validate the proposed methods, real production and sales data are sampled from a pharmaceutical plant. The case study shows that the improved production planning models are more targeted and effective for Chinese process industries.

Key concepts: Production (economics), Production planning, Process (computing), Weibull distribution, Function (biology), Key (lock), Operations research, Engineering

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