Supply Chain Simulation: A Survey

This paper provides a survey of simulation in supply chain management.It reviews four types of simulation, namely spreadsheet simulation, system dynamics, discreteevent simulation, and business games.Which simulation type should be applied, depends on the type of managerial question to be answered by the model.Moreover, this paper summarizes novel sensitivity and robustness analyses.This sensitivity analysis yields a shortlist of the truly important factors in large simulation models with (say) a hundred factors.The robustness analysis optimises the important factors controllable by management, while accounting for the noise created by the important non-controllable, environmental factors.Both analyses are illustrated by a case study involving the simulation of a supply chain in the mobile communications industry in Sweden.In general, simulation is important because it may support the quantification of the benefits resulting from supply chain management.simulation;logistics;performance measurement;risk analysis;uncertainty;bifurcation;supply chain management

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

Manufacturing Processes Management with Usage of Simulation Tools

Simulace výrobních procesů pomáhá optimalizovat výrobu, logistiku a další systémy, díky čemuž dochází ke snižování nákladů a racionalizaci vnitropodnikových procesů. Využitím diskrétní simulace programu Witness Power with Ease se v diplomové práci optimalizuje logistický tok materiálu ve společnosti Hella Autotechnik, s.r.o. Práce přibližuje metody a jednotlivé fáze tvorby modelu včetně jeho validace a navrhuje vylepšení, díky kterému by mělo dojít ke snížení nákladů na dopravní služby o 24 400 Kč měsíčně.By optimizing the logistics, production and other systems the simulation can reduce costs and rationalise business processes. By use of discrete simulation in software Witness Power with Ease is in this diploma thesis optimised logistical flow of material in the company Hella Autotechnik, s.r.o. The thesis introduces methods and particular phases of creating the model including its validation. The proposal in the diploma work suggests the improvement to lower the costs for the transportation services by 24,400 CZK per month.

Simulation study for investment decisions on the EcoBoost camshaft machining line

Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area. Keywords: simulation modelling, closed-loop network, automotive production system

DES Configurators for Rapid Virtual Prototyping and Optimisation of Manufacturing Systems

In the framework of the COPERNICO research project configurators were developed under the Siemens Tecnomatix Plant Simulation software environment, which support the rapid creation of the discrete event simulation (DES) models of several types of manufacturing systems. With the use of the configurators after defining the required input data – such as the product mix, production processes, layout prototype, etc. – the DES models of the manufacturing system alternatives will be automatically created. The layout prototypes are based on a cladistics classification of manufacturing systems. The aim of the configurators is not only to purely create the simulation models but also to create models that can be used for further optimisations, that can be done e.g. by using the built in genetic algorithms tool, based on specific objectives. In this paper some research results are demonstrated on how the configurators create DES models and how the models can be applied

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case