Importance of Software in the Manufacturing Industry

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Table of Contents

Introduction
Objectives
Grand challenges
Model design
References
Works Cited

Introduction

The manufacturing industry forms a great part of the economy in the world. There are however several challenges that must be addressed for the manufacturing industry to be a success (Fowler and Rose 470). The Injection Moulding Ltd, for example, is a manufacturing industry that has been producing desktop toys. It has however, been growing steadily and is planning to manufacture desktop products soon. The challenges that must be tackled are those to do with the costs of manufacturing and the time allocation.

Objectives

Certain objectives have been devised to assist the company deal with some of the issues that may affect its full functionality and effectiveness.

Time compression this is where the time required for production would be reduced to a reasonable amount.
Component integration this is the integration of the constituents of the system in order to assess their interactions.
Risk avoidance risks on finances or physical attributes to the system may be avoided using hypothetical models rather than the actual system itself.
Physical scaling this is the studying of a rescaled version of the actual system such that it would either be bigger or smaller than its actual size.
Repeatability this is where by various systems can be assessed in various environments or where a particular system may be studies in varying environments.
Control simulation of the environment enables it to be monitored accurately and be controlled effectively.

Grand challenges

A grand problem is a challenge that demonstrates certain characteristics that include the following:

The challenge would be difficult and for a solution to be arrived at, there must be the employment of one or several scales of improvement in ability and the use of several dimensions to ensure that.
Experts in the field should have proved the challenge unsolvable.
In the event that the solution is arrived at, it would lead to serious impacts either to the economy or socially.

The three characteristics discussed above face the manufacturing systems. The characteristics would be discussed in details below and the greatest challenge of the three would be discussed first.

Some of the processes that need to be executed in support of the decision-making process in manufacturing take long to design. These processes include the designing and collection of the relevant information. Building and execution follows then analysis of the simulation models concludes. This whole process ends up having fewer numbers of analysis cycles than it would be normally the case. There is however, a possibility to reduce the time required to collect and analyze the acquired data. In order to reduce the time allocation on data or information collection and data analysis, proactive data analysis can be done. Furthermore, the company could encourage discipline within the factory in order to maintain the existing information systems.

The time allocated to experimentation may be viewed in different perspectives that include the exploration of models that reduce the complex bits but at the same time provide accurate and liable results. Another perspective is the use of techniques that reduce variance. It may be through dividing in potions and using parallel simulation. A model design could be used to discuss the processes of manufacturing systems simulation.

Model design

Model designing is a critical stage that is usually ignored during the process of simulation. During this stage, there is the identification of the participants who participate in the project. The goals of the project are then laid down and the plan of execution developed. Some vivid descriptions of this process have been provided for in some literature. These descriptions have provided techniques that may help improve the design modeling process and increase the chances of having a successful project.

If the activities would not be followed to the latter, the likely result would be a detailed model. As much details can increase the objectivity and subjectivity of the model as fine detail may cause a model to be too difficult to build, comprehend, use and to maintain. The design stage should therefore dictate on the amount of details to include in the model. Experts in the field of simulation usually know the exact quantity of details to include in the model. A system may also be designed to keep the records of the past analyses and the amount of details utilized previously in order to help in the stage of designing the model.

The determination of how much details to include in the model may even become more appropriate and necessary when a manufacturing supply chain is to be designed. A lot has been already done in the design modeling of operations within the factory and the machine levels. However, little has been done in the level of the supply chain. In most occasions, models are employed in a specific level only and limited information is distributed between them. It would however, be appropriate to consider using the models to complement each other in the future. This would be achieved if several things were considered. Several aspects must be considered for this to be successful. This includes the utilization of the proper amount of abstraction for every model used. It should also be established whether both parallel and other simulation capabilities might be used. A proper method of sharing information between levels must be considered.

The next level is the development of the model which involves the building, verification and the validation of the model. The model approach used in the development of the model might not benefit the current project a lot but might be useful in the future during the designing and development of the models.

During the stage of model deployment, the major emphasis should be on the execution of the model in order to improve efficiency. The time taken by simulations to run in a system differs and may take little time in some. This is when the manufacturing system is simple. In complex systems, however, simulation may take a long time-a single replication taking as long as several hours.

References

The main problem that has been addressed in the discussion above is the absence of software that deals in real time simulation processes. It is much better to employ a different approach all together. This involves the developing of the model directly from the databases in the company rather than developing clones from the simulation model.

Most of the software that does simulation today enables models to be developed in different formats. It is because of this fact that this approach is not appropriate for decisions that require quick action to be taken. This is because the results should be readily available within the shortest time possible (minutes or seconds) after the problem has been identified. In order to make the required information readily available for use, it should be converted and stored in a format that allows quick retrieval for the simulation package.

Works Cited

Fowler, John, and Oliver Rose. Grand challenges in modeling and simulation of complex manufacturing systems. Simulation 80.9 (2004): 469-476. Print.

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