Contemporary Engineering Sciences, Vol. 8, 2015, no. 36, 1713 - 1719
HIKARI Ltd, www.m-hikari.com
http://dx.doi.org/10.12988/ces.2015.510292
Simulation of Concurrent Process Planning (CPP)
System for Machining Two Different Products
Bahaa M. Nasser
Industrial Engineering Department, College of Engineering
Northern Border University, Arar, Northern Border Region, Saudi Arabia
Copyright © 2015 Bahaa M. Nasser. This article is distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Abstract
In this paper, a simulation of a concurrent process planning (CPP) system is
introduced. This system consists of a main input: the production knowledge and
the production line. The production knowledge includes the production rules
related to generating the process plan from the part drawing. Two products are
used as output of the production knowledge and input for the manufacturing
center. The CPP simulation system indicates that the utilization of machining
center is very high and decreases the production cost. However, the waiting
number of products in the production line is low.
Keywords: Simulation, Modeling, Arena, Expert systems, process planning
system, concurrent process planning system, Production knowledge, computer
Aided Process Planning CAPP, production line
1 Introduction
Simulation is the control of a model in a manner that it works on time or
space to pack it, subsequently empowering one to see the collaborations that
would not generally be clear on account of their detachment in time or space [1].
While modeling and simulation generally are used to speak to a little parcel of this
present reality. Frameworks, for example, assemble plant with machines,
individuals, transport gadgets, carpet lifts, and storage room [2].
A CAPP-PPC serial and concurrent model process was presented in this
model the process plan was divided into three stages: thus are the initial process
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planning, process route planning and process specification planning. Also the
production planning was divided into three stages: factory level planning,
workshop level plans, and process level planning [3]. The CAPP-PPC concurrent
process can save production time, reduce production cost and improve the
production efficiency.
The Concurrent Process Planning (CPP) System is shown in figure 1. The
CPP system consists of the production knowledge of machining two products A
and B, the manufacturing center of drilling machine. The manufacturing center
lead to three stages: packaging, scraping and salvage.
Concurrent Process Planning (CPP) System
Production Knowledge
Product A
Product B
Manufacturing Center (drilling)
Package
Salvage
Scrape
Figure 1: Concurrent Process Planning (CPP) System
2 Ideas and strategies
The process plan can be defined as a recipe, which is a set of instructions for
transforming a raw material to a desired shape [4]. Process planning is considered
as the bridge between the engineering design and the manufacturing processes [5].
The basic function of process planning is to determine the sequence to be
followed in converting the work part from a raw material to a finished part or to a
desired shape [6]. The process plans must be developed within the equipment
capabilities and factory capacities. The concerned manufacturing engineers are
responsible to define the process plans according to the capabilities of the
available machines in the plant and the features of the product [7].
The implementation of Computer-Aided Process Planning (CAPP) system is
more appropriate for the batch production type [8]. Due to the rapid variation in
product types to accommodate the consumer's requirements, the CAPP system
becomes an essential tool for reducing the time and saving the human effort
consumed in the planning of the manufacturing processes [9, 10].
Simulation of concurrent process planning (CPP)
1715
The CPP System consists of two concurrent different products A and B: two
blocks: one has one hole and the other has two holes (Fig. 2). The first product,
named product A [Block (Length 100, width 100, Height 100) with hole
(Diameter 50, Depth 50)] is created in a contiguous division, outside the limits of
this model, with interval times to our model being exponentially distributed with a
mean of 5 minutes. The second units named product B [Block (Length 100,
width 100, Height 100) with two holes (Diameter 20, Depth 50)], is delivered in
an alternate building, additionally outside this present model's limits, where it is
held until a cluster of three units is accessible; the bunch is then sent to the last
creation region we are demonstrating. The time between the entries of progressive
groups of product B to our model is exponential with a mean of 30 minutes.
At the drilling machining center, the products A and B are embedded, the
case is amassed and fixed, and the fixed unit is tried. The aggregate procedure
time for these operations relies on the part sort: Triangular Distribution TRIA (1,
3, 6) for product A and Weibull Distribution WEIB (2, 5) for product B (2 is the
scale parameter β and 5 is the shape parameter α). Ninety percent of the products
pass the investigation and are moved directly to the packaging division. The
remaining parts are switched to the re-drilling work area. Eighty percent of these
products are scrap and the rest are rework and moved to the packaging division as
revised parts, and the rest are exchanged at the scrap region. An ideal opportunity
to improve a section takes after an exponential conveyance with mean of 30
minutes and is free of part sort and a final manner.
3 Building CPP Model
A simulation model is the main step to build a simulation project. The
simulation model of CPP system is shown in figure 3. This model was built in arena
software using these modules: two create, two assign, four processes, two decide,
three records, and three dispose.
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Figure 3. The simulation model of CPP system
The following Tables include the main data
Name
Product A arrive
Product B arrive
Entity Type
Product A
Product B
Create Modules
Type
Value
Random (Expo)
5
Random (Expo)
30
Assign Modules
Name
Type
Assign Product A Drilling and arrive time
Assignments
Attribute
Attribute
Assign Product B Drilling and arrive time
Assignments
Attribute
Attribute
Units
Minutes
Minutes
Entities/Arrival
1
4
Attribute Name
New Value
Drilling Time
Arrive Time
TRIA(1,3,6)
TNOW
Drilling Time
Arrive Time
WEIB(2, 5)
TNOW
Process Modules
Name
Prim A process
Action
Seize Delay
Release
Prim B process
Seize Delay
Release
Drilling Process
Seize Delay
Release
ReDrilling
Process
Seize Delay
Release
Type
Resources
Resource Name
Quantity
Delay Type
Resource
Type
Prim A
Resource Name
1
Quantity
TRIA(1,4,8)
Delay Type
Resource
Type
Prim B
Resource Name
1
Quantity
TRIA(3,5,10)
Delay Type
Resource
Type
Drilling
Resource Name
1
Quantity
Expression
Delay Type
Resource
ReDrilling
1
EXPO( 45)
Decide Modules
Name
Type
Failed Drilling Inspection
2-way by chance
Failed ReDrilling Inspection
2-way by chance
Percent True
8%
25%
Simulation of concurrent process planning (CPP)
Name
Record Scrapped Blocks
Record Salvaged Blocks
Record Packaging Blocks
Record Modules
Type
Attribute Name
Time interval
Arrive Time
Time interval
Arrive Time
Time interval
Arrive Time
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Tally Name
Record Scrapped Blocks
Record Salvaged Blocks
Record Packaging Blocks
Dispose Modules
Name
Scrapped
Salvaged
Packaging
At the run setup window, working hours per days is 16 and replication
length is 5 days.
4 Statistical Analysis of CPP System
Some of the selected result of the CPP simulation system can be illustrated
in the following Tables. Table 1 shows the difference between the number of
input and output products for each process center: Product A, Product B, Drilling
and re-Drilling, and the percentage between the output products to the input
products at each process center.
Process Center
Drilling Process
Product A process
Product B Process
ReDrilling Process
Number of input
Products
1654
1023
648
142
Number of output
Products
1651
1009
645
99
Table 1 Process Center
Output percentage
of products
99.82%
98.63%
99.54%
69.72%
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Output percentage of products
Number of input & output products
Output percentage of…
Number of input Products
1654 1651
99,82%
1023 1009
98,63%
99,54%
69,72%
648 645
142
Drilling
Process
Product A
process
Product B
Process
99
Drilling
Process
ReDrilling
Process
Product A
process
Product B
Process
ReDrilling
Process
In Table 2 shows the average and the maximum waiting number of products per
second.
Queuing Process
Average Waiting Number of Products
Maximum Waiting Number of Products
Drilling Process.Queue
0.81
6
Product A process.Queue
4.55
23
Product B Process.Queue
5.72
31
ReDrilling Process.Queue
23.04
46
Table 2 Queuing Process
Waiting Number of Products in CPP System
46
Average Number of Products
23,04
31
23
5,72
ReDrilling Process.Queue
Maximum Number of Products
Product B Process.Queue
4,55
Product A process.Queue
6
0,81
Drilling Process.Queue
5 Conclusions
By using the concurrent CPP simulation system to simulate the production
lines indicates that the utilization of machining center comes up to 99.82%, and
lead to decreasing the production cost. Also, the waiting number of products in
production line not more than 6 products per second.
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Received: November 4, 2015; Published: December 14, 2015