Master production schedule time interval strategies in make-to-order supply chains¶

Este artigo apresenta uma proposta de sistema de controle da produção para regular o fluxo de materiais de pequenas e médias empresas fabricantes de calçados que adotam a política de atendimento à demanda RTO (resources-to-order) ou MTO (make-to-order), trabalhando com uma ampla variedade de produtos finais. Para entender a problemática do PCP (planejamento e controle da produção) nesse segmento, foram pesquisadas 7 fábricas de calçados localizadas na cidade de Birigui-SP. A proposta engloba: a) a escolha de um ordering system (sistema de coordenação de ordens (SCO)); b) desenvolvimento de um método para elaboração do programa mestre de produção MPS (master production schedule); e c) procedimentos para seqüenciar as ordens de produção.

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The Master Production Schedule

Mrp II ◽

10.1007/978-1-4615-4117-2_4 ◽

1996 ◽

pp. 40-58

Author(s):

John W. Toomey

Keyword(s):

Production Schedule ◽

Master Production Schedule

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An improved Genetic Algorithm For Fuzzy Production PlanningProblems with Application

Journal of University of Human Development ◽

10.21928/juhd.v1n3y2015.pp390-396 ◽

2015 ◽

Vol 1 (3) ◽

pp. 390

Author(s):

Jalal Abdulkareem Sultan ◽

Omar Ramzi Jasim ◽

Sarmad Abdulkhaleq Salih

Keyword(s):

Genetic Algorithm ◽

Customer Service ◽

Fundamental Problem ◽

Demand Forecasting ◽

Fuzzy Model ◽

Main Idea ◽

Production Schedule ◽

Improved Genetic Algorithm ◽

Customer Service Level ◽

Master Production Schedule

Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problem in operation and it can potentially lead to poor customer satisfaction. In this paper, an improved Genetic Algorithm (IGA) is used to solving fuzzy multi-objective master production schedule (FMOMPS). The main idea is to integrate GA with local search operator. The FMOMPS was applied in the Cotton and medical gauzes plant in Mosul city. The application involves determine the gross requirements by demand forecasting using artificial neural networks. The IGA proved its efficiency in solving MPS problems compared with the genetic algorithm for fuzzy and non-fuzzy model, as the results clearly showed the ability of IGA to determine intelligently how much, when, and where the additional capacities (overtimes) are required such that the inventory can be reduced without affecting customer service level.

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ANALISIS PERENCANAAN BAHAN BAKU DI UD. AA DENGAN MENERAPKAN METODE MATERIAL REQUIREMENT PLANNING (MRP)

Jurnal Logistik Indonesia ◽

10.31334/logistik.v5i1.1180 ◽

2020 ◽

Vol 5 (1) ◽

pp. 1-12

Author(s):

Rudi Abdika Saputra ◽

Inna Kholidasari ◽

Susanti Sundari ◽

Lestari Setiawati

Keyword(s):

Lot Sizing ◽

Raw Materials ◽

Raw Material ◽

Production Schedule ◽

Material Requirements Planning ◽

Forecasting Method ◽

Material Requirement Planning ◽

Material Requirement ◽

Material Procurement ◽

Master Production Schedule

This study discusses the application of the material requirements planning (MRP) method in the planning of raw materials in a furniture company. The purpose of this research is to know the planning of raw materials for furniture products in UD. AA, determine the most suitable inventory model to be applied to material inventory planning and analyze the role of the MRP system in raw material procurement planning. The forecasting method used is the quantitative method of time series analysis, determining the master production schedule, calculating lot sizing (LFL, EOQ, POQ methods). From determining the Master Production Schedule, it is found that the cabinet production plan for the next three months is 4 units per period or week, and based on the calculation of Material Requirement Planning (MRP) it can be seen what components are needed for the manufacture of cabinets, how many and when each component is required. Therefore it is obtained that the total raw material requirement for wood for the next three months is 11.34 m³.

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