Simulation of Less Master Production Schedule Nervousness Model

Abstract

In production decision making systems, Master Production Schedule (MPS) states the requirements for individual end items by date and quantity. The solution sensitivity to demand forecast changes, unforeseen supplier and production problem occurrences, is known as nervousness. This feature cause undesirable effects at tactical and operational levels. Some of these effects are production and inventory cost increases and, also, negative impacts on overall and labor productivity. To tackle this problem, we proposed a Mixed Integer Programming (MIP) model where nervousness reduction is carry out finding minimal suboptimal solutions. We perform a simulation under rolling planning horizon environment considering stochastic demand. Results of simulation show that, at each time demand changes take place the model can adjust the solution to achieve less nervousness without a significative change in cost performance.

A product-driven system approach for multilevel decisions in manufacturing planning and control

“…Stability is achieved at the tactical level using a nervousness measure (Herrera & Thomas, 2009) which quantifies the variation in the planned quantities on a weekly basis. Some results consider the distributed decision and others disregard the distributed decision.…”

“…(1) Tactical level: It uses an integer programming model that defines quantities as produced by item and period in a rolling horizon (Herrera & Thomas, 2009). Quantities are divided into sublots during the first period, and the sequence to be used in the manufacturing process must be defined using an integer programming model that solves the lot-streaming problem.…”

Fuzzy-FMEA Theory Approach for Prioritizing Supply Chain Nervousness Factors

“…Problem Addressed Methodology [25] Nervousness in MRP systems under uncertainty Simulation modeling [26] Quantify nervousness in stochastic inventory control demand Rolling horizon planning procedure [27] Examining solutions for overcoming master production schedule nervousness Simulation model [28] Exploring undesirable effects of nervousness master production scheduling Simulation and mixed-integer programming model [29] Addressing the implications of the statistical findings compared to simulated MRP environments Simulation model [30] Considering the economic effect of the production schedule caused by nervousness Wagner-Whitin method [31] Stochastic lot sizing nervousness problem Mixed-integer programming [32] Unveiling SCN and presenting a strategic framework for disruption management under a fuzzy environment Fuzzy-DEMATEL [33] SCN analysis Fuzzy-ELECTRE [9] Introduction of global supply chain nervousness (GSCN) Delphi-fuzzy-AHP…”

Proposición de una arquitectura holónica basada en productos inteligentes para el aumento de la flexibilidad en planificación de la producción y logística.

“…Los PDS sumados a productos inteligentes entregan autonomía y crean nuevas oportunidades de mejora en reactividad y agilidad, debido a la descentralización de la toma de decisión y la generación de soluciones en cortos periodos de tiempo. Los productos inteligentes y los PDS pueden coexistir de forma dinámica y temporal, o incluso ser parte de las coordinaciones en los diferentes niveles de la empresa (Herrera et al, 2010). El modelo propuesto muestra que la coordinación entre las entidades de un sistema productivo es factible y destaca la importancia de la reactividad en la toma de decisiones para la generación de ambientes productivos más estables.…”