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Evaluation of Production Schedule in Smart Factory

Evaluation of Production Schedule in Smart Factory

We should complete customized products in
specified time to implement smart factories. For this simulation
can work as a tool for validating production schedule. We
propose in the manuscript a simulation model for sewing
machine and modeling tool for simulation of sewing process.

Industrie 4.0, proposed by DFKI [1], is defined as the 4th
industrial revolution based on Internet-of-Things (IoT) [2],
cyber-physical systems (CPS) [3], and Internet-of-Services
(IoS) [4]. One of the characteristics of Industrie 4.0 is that it
includes smart factories capable of generating customized
products for customers. One of the important issues to
implement a smart factory is to complete and deliver
customized products to customers within specified time. For
this, we need an efficient scheduling algorithm [5].
It becomes more and more sophisticated work to validate a
production schedule in factories. Simulation is a tool for
validating a production schedule and changing it if needed. For
using simulation, we need appropriate simulation models. In
this paper, we propose a sewing machine model for simulating
sewing process. The proposed sewing machine model includes
sensing, sewing, forwarding and control functions as
submodels. Also, we propose a modeling tool that includes the
proposed model. The proposed modeling tool manages a model
library that can be continuously extended for sewing process
simulation. Further, it can automatically generate and build
source codes for simulation models. Therefore, users can easily
develop their own models and simulate them.
II. SIMULATION MODEL FOR SEWING PROCESS
A. Motivation
One of the distinguishing features of smart factories
compared to existing factories is that the smart factories
generate customized products. Other characteristics of a smart
factory are as follows [6-8].VS sewing machine
1) Each product has a unique ID. 2) Each product passes a
different sequence of processes until all required processes are
completed. 3) Products and facilities communicate with each
other to determine each product’s production schedule.
Therefore, facilities in the smart factories should be modeled
differently than facilities in existing factories.
B. Sewing machine model (Structural model)
We defined a sewing machine model for simulating sewing
machine processes. Figure 1 shows the structure of the
proposed sewing machine model.
Fig. 1. Sewing machine model (Structural model)
The sewing machine model was defined as a structural
model consisting of four component models (Sensor / Work /
Forward / Control). Sensor model detects raw material or semifinished
products arrived at the sewing machine.

Evaluation of Production Schedule in Smart Factory


products. Forward model chooses the next forwarding
facility and passes the processed semi-finished product on the
selected next facility. Finally, Control model governs the
whole operations of the sewing machine.
C. Sensor model (Behavioral model)
Sensor model abstracts a sensor module that detects raw
material or semi-finished products arrived at the sewing
machine. Figure 2 illustrates the state transition diagram of the
sensor model.
Fig. 2. Sensor model (Behavioral model)
Sensor model has 4 phases and moves from one phase to
another whenever state transition occurs. The Sensor model in
Init phase stores its current location and moves to the Sensing
phase. In Sensing phase the Sensor model periodically checks
whether semi-finished products has been arrived at the sewing
machine. If there is one, it goes to Detected phase. Otherwise,
it goes to Non-detected phase. In Detected phase the Sensor
model outputs the information of arrived product through the
port Out_Sensor_Detection and then returns to the Sensing
phase. In Non-detected phase it returns to the Sensing phase
after a predefined time.
D. Work model (Behavioral model)
Work model represents the sewing operation and changes
the properties of an arrived product. Figure 3 shows the state
transition diagram of the Work model.
Figure 3 Work model (Behavioral model)
Work model has 3 possible phases (Idle, Working,
Reporting). In Idle phase, it waits for a product to arrive at the
sewing machine. When an input is arrived through the port
In_Work_Command, the Work model moves to the Working
phase. It changes the properties of the arrived product in
Working phase and outputs the work result through the port
Out_Work_Report.
E. Forward model (Behavioral model)
Forward model implements a variable process of a smart
factory by choosing the next forwarding facility for a semifinished
product and delivers the product to the selected facility.
Figure 4 represents the state transition diagram of the Forward
model.https://www.vssewingmachine.in/

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