# Activity Cycle Diagram And The Condition Specification Computer Science Essay

Published:

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

Many descriptive and symbolic techniques for representation of the simulation of a model are present in literature. Some of these techniques are better with one model while not better with the representation of the other one. Two most important techniques for representation of model simulation are known as Activity Cycle Diagram and the Condition specification. The activity cycle diagram (ACD) has been used an ideal technique to represent a model. The technique is based on Tocher's idea of stochastic gearwheels (quoted in Paul et al 1993. The ACD represents the activities of a model with its entities by composing their life cycles. The entity could be a passive state as Queue or an active state as activity. The Queue and activity are represented in ACD with specific symbols.

Part A

## Specification of the model domain

A part enters a cell where it is first loaded onto machine 1. After this operation the part is either loaded immediately on to machine 2, or if that machine is busy, it is moved to a buffer area. After the operation on machine 2, the part leaves the system. All movements are carried out by a robot.

The entities in the system and their possible states.

## A part

Enters into cell

Move to buffer if machine is busy

Leaves the machine after operation by machine 2

## Machine 1

One in number

First in activity

No waiting for part to enter in machine 1

## Machine 2

One in number

Second or Third in activity

No waiting or waiting for part to enter in machine 2

## A Robot

Moves a part from position zero to machine 1

Moves a part from machine 1 to machine 2 or to buffer zone if

machine 2 is busy

Moves a part from buffer zone to machine 2 when machine 2 is ready.

## A buffer area

Stores a part when machine 2 is busy

Don't store a part if machine 2 is ready

Move a part from buffer area to machine 2 when machine 2 is ready

## Classes of Entities

Permanent entities stay in system ; Machine 1 & Machine 2, Robot

Temporary entities that move through the system â€¦Part, Buffer zone

1.2 The Activity Cycle Diagram for each of the entities.

## 2

Machine 1 Enter into Machine 1

## Figure 6

Part B

The elements of the Activity Cycle Diagram that introduce the parts in the cell.

Robots are the elements of ACD that introduce parts into machines. It is assumed that there are two Robots. Robot 1 introduce part into machine one and then it has two choices. It moves part from machine 1 to machine 2 if machine 2 is ready to uptake the part. In case the machine 2 is busy, the Robot 1 moves part from machine 1 to buffer zone which is a waiting area.

The Robot two is assumed to work with machine 2. It moves part from buffer area into machine 2 when machine 2 becomes available. After processing in machine 2, the Robot 2 moves part from machine 2 to its final position.

It should be noted that some assumptions have been made for the responsibilities of two elements (Robots) provided exact tasks have been provided.

Four bullet points of the key aspects of proposed diagram.

## The conditions on which the particular activities in your diagram will be executed.

Each activity in ACD is bound with some condition or conditions. For example, in the activity of moving part from machine 1 to machine 2, the attached condition is availability of the machine 2. The Robot 1 will move part from machine 1 to machine 2 provided machines 2 is available to uptake the part. If the condition changes and machine 2 is busy, then Robot 1 will move part to buffer zone.

The other significant activity of ACD is related to moving part from buffer zone to machine 2. It is assumed to be done by Robot 2. The Robot 2 has two choices or it will be dealing with two conditions. In condition one when machine 2 is busy, The Robot 2 will not move part from buffer area to machine 2. In condition 2 when machine 2 has become available, then the Robot 2 will move part from buffer zone to machine 2.

In the third significant activity, the Robot 2 will move part from machine 2 to its final stage conditional that machine 2 has finished its job on the part. In short, each activity in an ACD is related to one or more conditions.

## The main attributes of your entities

The ACD represents the activities of a model with its entities by composing their life cycles (Abdul et al 1994). The entity could be a passive state as Queue or an active state as activity (Sawhney et al 1995). The Queue and activity are represented in ACD with specific symbols (Shi et al 1997).

In the current example, there are also two entities. One is the actual activity or the active state like moving Part from machine one to machine 2 and other entity is the passive entity like buffer zone which can be said as the queue. Similarly we can look at the total entities in ACD. In current example, entities are machine 1, machine 2, Part, buffer area, robot.

## The physical realization of the queues in the system

The physical activity diagram presents an obvious picture to observe the queues in the system (Zeigler 1987). The physical realisation of the queues in the current example comes from the buffer zone which is used as a queue in the example. The part has to wait in buffer area when machine 2 is not free. Therefore the buffer are presents a realisation of the physical queue.

## The outcome parameters to be studied by the model built upon activity cycle diagram.

Each model is designed to study certain parameters in the model (Halpin 1977). The simulation even not used primarily for the optimization of parameters is helpful in optimizing the model in joint effort with design analysis and mathematical evaluation. In the current study, the potential parameters which can be a focus of the study may be studying of queues at buffer zone level, Rate of feed at machine 1, rate of part flow from machine 1 to machine 2 and the removal rate of part from machine 2. All these parameters are of quite significance. For example any significant delay at queue (at buffer zone), decrease at the feed rate at machine 1 or delay at removal rate of part at machine 2 can disrupt the Cell function or decrease its efficiency.

The kind of simulation experiments that would be performed with the model.

In the real world experimentation can be expensive and in manufacturing and production system, many resources may be used in experimentation (McCahill et al 1993). The alternative to expensive experimentation is simulation methods and other analytical methods (Nance et al 1988). Especially computer model simulations may be economical and provide a chance of actual system observation without incurring unacceptable and expensive options (Murata 1989). On the other hand, physical models may not provide a real picture especially where a layout of resources requires examination such as productivity flow (Vanegas et al 1993). In complex and multistage problems, it may become complex to conduct real and physical experimentation (Paulson 1978). Some actions and activities are not even possible in real world such as a process like flow line optimisation where blocking of a system is required but practically very hard to follow (Paulson et al 1987). However, simulation is not an optimisation procedure and must be supported with other procedures like design analysis and optimisation. Therefore we can use experiments like optimisation, design analysis, computerisation simulation, manual simulation, and mathematical model analysis.

In current example, objective of model will be kept in mind. First of all small models will be built for each entity. Model will be built in phases and each phase will be checked if it is working properly. The model will be made in phases as it is shown in individual ACD examples. The final ACD will be built once the individual ACD for each entity are checked. Each ACD if planned on computer model or manually will be debugged and corrected.

Conclusion

ACD are actually the significant evaluation of the flow chart design but with additional features of being used in production and manufacturing field by simulation process. Software is used in designing, analysis and simulation process. Each ACD has entities, attributes attached with entities and conditions associated with each activity. ACD is developed by designing individual ACD for each activity separately and then analysis them for correction. The whole model ACD is developed by merging individual ACD. The current assignment has provided a chance to understand the process of ACD development and analysis by working from individual ACD to the ACD of whole model.

References

Abdul Riaz, S., Shi, j. 1994. Automated construction simulation optimization. J Construction Eng and Management. ASCE. 120(2), 374-385.

Halpin, D.W.1977. Cyclone. A method for modeling job site processes. J Construction Eng and Management. ASCE. 103(3), 489-499

McCahill, D.F., L.E.Bernold.1993. Resource oriented modeling and simulation in Construction. J Construction Eng and Management. ASCE.119 (3), 590-606.

Murata, T.1989. Petri nets. Properties, Analysis and implications. Proceeding of IEEE. 77(4).541-580.

Nance, r.e, Overstreet .C.M. 1988. Diagnostic assistance using digraph representations of discrete event simulation model specifications. Transactions of the society for computer simulation. 4(1).33-57.

Paulson, B.C.1978. Interactive graphics for simulating construction operations. J. Construction. Div. ASCE. 104(1), 69-76.

Paulson, B.C., Chan, W.T., Koo, C.C.1987. Construction Operations simulation by microcomputer. J Construction Eng and Management. ASCE.113 (2), 302-314.

Sawhney, A., S.M. AbouRiaz.1995. Simulation based planning method for construction project. J Construction Eng and Management. ASCE. 121(3). 297-303.

Shi, J., S.AbouRizk.1997. Resource based modeling for construction simulation. J Construction Eng and Management.

Vanegas, J.A., E.B.Bravo., D.W.Halpin.1993. Simulation Technologies for planning heavy construction processes. J Construction Eng and Management. ASCE.119 (2).336-354.

Zeigler .B.P. 1987. Hierarchical modular discrete event modeling in an object oriented environment. Simulation. 49(5).219-230.