The need for simulation in complex industrial systems

Production Planning & Control, 2011

2012

The paper presents a simulation on automotive inventory and stock issue, followed by evaluated performance of automotif Sector Company, focused on getting optimum profit from supply and demand balancing. Starting by evaluating and verification of customer's document until car delivered to customer. Simulation method of performance is used to evaluate company activity. excess demand of car by customer, not eligible customer to rented a car, number of customer who served and number of customer who served including the driver, the last result is number of optimum demand that match with the stock or supply of car by the company. Finally, board of management should be making decision; the first decision is buy the new car for meet with the demand or second decision is recruit new staff for increasing customer service or customer care.

2009

The production costs reduction in a highly competitive environment is a critical success factor. In particular, in fields where outsourcing is used frequently and the impact of the material costs is high, a significant cost reduction can be achieved making more efficient value chain. Moreover, the use of outsourcing is a way to adjust production capacity depending on demand. Therefore the coordination and planning of the various rings of the chain and the estimate of the productive capability of the various production units become fundamental for a coherent evaluation of promised delivery times. More and more frequently and in greater detail the Companies at the "end of the network" require, through capacity assessment a verification of the available productive capacity of the manufacturing units, both from a quality and quantity point of view, that each single firm can dedicate to a certain type of production. In this paper it is presented a simulation model that allows the elaboration of an operative plan of production through the verification of finite capacity scheduling of resources. The model tends to minimize costs of stocking and setup , considering other production costs as constant. The simulation is a technique that allows the checking with better precision of the use of the resources with variation of the ties. This approach lead to a high performing instrument in the field of the advanced planning and scheduling through analysis of the various possible views. The auxiliary use of the optimizing tool available in the ARENA software allows an optimal solution, confirming the validity of the study of new applications of the simulative instrument for the verification of productive capacity in the short term.

This paper describes importance of simulation as a handy tool in today’s techno-commercial business environment. To strive in global market, organisations are trying to improve their performance using various optimisation tools and techniques available. Instead of evaluating every alternative in real world, simulation helps to mimic various alternatives available for optimisation and on the basis of these results decision making becomes very easy. Under the cost reduction objective, company has decided to localise i.e. manufacture sub-assemblies inhouse which were been imported previously. Localisation project will add new workstations in the existing assembly line. To ensure that the modified assembly line is optimized, various alternatives for newly added workplace as well as different worker allocation patterns were evaluated using simulation software. These results strengthen the proposal in decision making process.

2012

In this work, we propose a hybrid simulation optimization approach that addresses the problem of supply chain management. We formulated the problem as a mathematical model which minimizes the summation of production cost, transportation cost, inventory holding and shortage costs, subject to capacity and inventory balance constraints and propose a hybrid approach combining mathematical programming and simulation model to solve this problem. The main objective of this approach is to overcome the computational complexity associated with solving the underlying large-scale mixed integer linear problem and to provide a better representation of supply chain reality. The simulation-based optimization strategy uses an agent-based system to model the supply chain network. Each entity in the supply chain is represented as an agent whose activity is described by a collection of behavioral rules. The overall system is coupled with an optimization algorithm that is designed to address planning and scheduling level decisions.

2010

T he competitiveness and dynamic nature of today's marketplace is due to rapid advances in information technology, short product life cycles and the continuing trend in global outsourcing. Managing the resulting supply chain networks effectively is challenged by high levels of uncertainty in supply and demand, confl ict objectives, vagueness of information, numerous decision variables and constraints. With such levels of complexity, supply chain optimisation has the potential to make a signifi cant contribution in resolving these challenges. In this paper, a literature review -based on more than 100 peer-reviewed articles -of state-of-the-art simulation-based optimisation techniques in the context of supply chain management is presented. A classifi cation of supply chain problems that apply simulation-optimisation techniques is proposed. The main criteria for selecting supply chain optimisers are also identifi ed, which are then used to develop a map of optimisation techniques. Such a map provides guidance for researchers and practitioners for a proper selection of optimisation techniques.

This presentation covers different phases of the manufacturing system life cycle. Starting from conceptual system design to planning of operations. Material handling and logistic are the key factors in modern networking manufacturing. The author proposes use of discrete event simulation as a system design and operation-planning tool. Traditionally simulation tools have been used in the system planning and design; today the simulation models are used in all the different phases of manufacturing system life cycle. This paper presents two case studies. First case shows a modular semiautomatic assembly system planning using simulation. Second case presents a simulation tool developed for operations planning, management of production capacity and decision helping for planning of operations.

Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304)

Industrial & Engineering Chemistry Research, 2006

This work presents a novel approach that addresses the management of chemical supply chains (SCs) under demand uncertainty. One of the main objectives is to overcome the numerical difficulties associated with solving the underlying large-scale mixed integer nonlinear problem (MINLP). The approach that is proposed relies on a simulation-based optimization strategy that uses a discrete-event system to model the SC. Within this framework, each SC entity is represented as an agent whose activity is described by a collection of states and transitions. The overall system is coupled with an optimization algorithm that is designed to improve its operation. This strategy is a very attractive alternative in the field of decision-making processes under uncertainty, the advantages of which are highlighted with some cases of SC networks that are composed of several plants, warehouses, distribution centers, and retailers.

1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274)

In business today, re-engineering has taken a great deal of the cost out of internal corporate processes. Our factories and internal support organizations have become much more efficient, but there is still a great deal of unnecessary cost in the overall delivery system, or the supply chain. Although your corporation does not own all of the supply chain, the entire chain is responsible for product delivery and customer satisfaction. As one of several methodologies available for supply chain analysis, simulation has distinct advantages and disadvantages when compared to other analysis methodologies. This paper discusses the reasons why one would want to use simulation as the analysis methodology to evaluate supply chains, its advantages and disadvantages against other analysis methodologies such as optimization, and business scenarios where simulation can find cost reductions that other methodologies would miss.