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Factory Data Collection System ( FDC )
 Various techniques are used to collect data from the factory floor.
These technique range from clerical methods that requires workers to
fill out paper forms that are later compiled, to fully automated
methods that require no human participation.
 The FDC system consists of the various paper documents ,terminals,
and automated devices located throughout the plant for collecting
data on shop floor operations, plus the means for compiling and
processing the data.
 The data collection system also include the time clocks used by
employees to punch in and out of work.
 Even though a modern FDC system is largely computerized, paper
documents are still used in in factory operations and our coverage
includes both manual(clerical) and automated systems.
 The ultimate use of the factory data collection system is twofold :
(1) to supply status and performance data to the shop
control system.
(2) to provide current information to production foreman,
plant management and production control personnel.
• To accomplish this purpose , the FDC system must input data to the
plant computer system.
 In most cases, this data is collected manually and entered into the system
by a human operator.
 The three common problems with manually collected data are
untimeliness, inaccuracy, and bias. Considering that this raw data forms
the basis for all subsequent production reports - and that important
decisions are made based on those reports - any problems with the initial
data collection can start a ripple effect that results in a negative impact on
your business.
 Automatic shop floor data collection allows you to make better business
decisions.
Manually collected data is not timely
In a typical scenario, manually collected production data is entered into the
system only at predetermined times such as at the end of a shift or job. The
data is then made available in the form of reports and used for analysis. For
long-term analysis, viewing the data “after the fact” is usually sufficient.
However, the factory floor is a dynamic environment, and only knowing
what happened after the fact can be a
detriment to productivity. Consider the following:
 When a machine goes down, how long does it take maintenance personnel
to respond?
 Do the people responsible for material handling know when a machine is
starved for raw material?
 If a machine is down for an extended period of time, is the scheduler able
to quickly respond and modify workflow to keep jobs moving through the
queue?
Manually collected data is inaccurate
There are many opportunities for inaccuracies to creep into a manual data
collection system. Often the data must be first written down, and later entered
into the system – sometimes by a different person than the one that recorded it in
the first place. Typographical and transcription errors are common. Human error
is inevitable, and once these errors become part of the data set, they become
difficult to detect and eradicate, and make all the resulting reports suspect.
Manually collected data is biased
Whenever a human operator enters data, he or she has influence over exactly what
information is entered and when it is entered. Consider the following example:
Let’s say that the controller on Machine Number 1 detects an easily correctable problem
and sops the machine. Let’s also say that the operator responsible for Machine Number 1
is busy elsewhere in the plant, and Machine Number 1 sits idle for an hour while the
operator is otherwise occupied. When the operator is finally free, he spends 5 minutes
fixing the problem, and then restarts Machine Number 1. Even though he was busy with
another machine, the operator is worried that he’ll be disciplined for not attending to
Machine Number 1 quickly enough, so he logs “Tooling problem – 10 minutes” as the
reason for downtime.
Automated Data Collection System
Fortunately, a number of factors have combined to make automatic data collection
technology much more reliable and accessible:
 The emergence of high speed Ethernet as the de facto standard for local area networks has
resulted in a tremendous decrease in the cost of network cards, adapters, and other
hardware, thus allowing Ethernet to replace the out-dated, slow, and expensive dedicated
serial networks.
 It turns out that the Internet and email were not passing fads after all. Virtually all
computers are now shipped with a web browser and an email client. Data collection
software can now use a web browser to display and manipulate data and email to distribute
reports. This has eliminated the need to install maintenance-intensive client software on
workstations.
 Database manufacturers adopted Structured Query Language (SQL) as a means to get data
in and out of various databases. This makes it much easier for different software packages
to share data, and allows an SQL-based data collection system to provide data to MES and
ERP software.
 It is now easier to communicate with the equipment. Microsoft and the automation
suppliers got together and developed a set of standards (called OPC – described below)
that allows for interoperability of different devices.
Requirements of a good data collection system
 A modern data collection system is composed of a data logger/transaction manager, a
database, a report generator, and a factory viewer real-time interface. These programs
typically operate together on a single server
 The two “client” portions are made up of an email client (such as Microsoft Outlook) to
receive reports, and a web browser (Internet Explorer, Firefox, Navigator, etc) to display
the factory viewer portion.
 The web browser acts as the “front end” to the system. It is used to view real time data as
well as for setup and maintenance, security access, etc.
 The heart of the data collection system is the data logger. The data logger is a program that
gathers the raw production data, organizes it, and puts it in a database. There are two
different data logging methods that can be employed by data collection systems. These are
distributed data loggers and centralized data loggers.
 In a distributed system, a data logger is installed on each machine. The data logger collects
production data directly from the machine, stores it in memory, and periodically sends it
off to the data repository (usually a database).
Advantages and Disadvantages:
 The advantage of a distributed system is that in the event of a network outage, the on-board
data logger can continue to collect production information from the machine while the
network is down, and then “backfill” the database when the network comes back up.
However, the disadvantages of a distributed system outweigh this one advantage:
 Since distributed data loggers do not continuously update the database, you cannot view the
production environment in real time.
 Data logging capability cannot easily be retrofitted into existing controllers. The hardware
requirements for a data logger typically include multiple processors and significant on-board
memory. Most existing machine controllers do not have the spare “horsepower” to run a data
logger. In almost all cases, a separate dedicated (usually expensive) data logging device
must be installed on each production machine.
 Maintenance is more difficult with distributed systems. Inevitably, there will come a time
when it will become necessary to upgrade/update the data loggers. This is usually triggered
by changes in the Windows operating system. Instead of simply updating a single data
logger (as you would in a centralized system) you must update every individual machine.
 When it’s time for the distributed data logging devices to upload their information to the
database, the resulting spike in network traffic has the potential to adversely affect your
LAN.
Data collection terminal Data collection system components
Some of the configuration of data collection terminal that can be installed in
the factory include :
 One Centralized terminals
 Satellite terminals
 Workstation terminals
The trend in industry is towards more automated factory data collection.
Although they are called “automated", many of the techniques require the
participation of human workers, so data collection system has included
“semi-automated”.

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Computer integrated manufacturing

  • 1.
  • 2. Factory Data Collection System ( FDC )  Various techniques are used to collect data from the factory floor. These technique range from clerical methods that requires workers to fill out paper forms that are later compiled, to fully automated methods that require no human participation.  The FDC system consists of the various paper documents ,terminals, and automated devices located throughout the plant for collecting data on shop floor operations, plus the means for compiling and processing the data.  The data collection system also include the time clocks used by employees to punch in and out of work.  Even though a modern FDC system is largely computerized, paper documents are still used in in factory operations and our coverage includes both manual(clerical) and automated systems.
  • 3.  The ultimate use of the factory data collection system is twofold : (1) to supply status and performance data to the shop control system. (2) to provide current information to production foreman, plant management and production control personnel. • To accomplish this purpose , the FDC system must input data to the plant computer system.  In most cases, this data is collected manually and entered into the system by a human operator.  The three common problems with manually collected data are untimeliness, inaccuracy, and bias. Considering that this raw data forms the basis for all subsequent production reports - and that important decisions are made based on those reports - any problems with the initial data collection can start a ripple effect that results in a negative impact on your business.  Automatic shop floor data collection allows you to make better business decisions.
  • 4. Manually collected data is not timely In a typical scenario, manually collected production data is entered into the system only at predetermined times such as at the end of a shift or job. The data is then made available in the form of reports and used for analysis. For long-term analysis, viewing the data “after the fact” is usually sufficient. However, the factory floor is a dynamic environment, and only knowing what happened after the fact can be a detriment to productivity. Consider the following:  When a machine goes down, how long does it take maintenance personnel to respond?  Do the people responsible for material handling know when a machine is starved for raw material?  If a machine is down for an extended period of time, is the scheduler able to quickly respond and modify workflow to keep jobs moving through the queue?
  • 5. Manually collected data is inaccurate There are many opportunities for inaccuracies to creep into a manual data collection system. Often the data must be first written down, and later entered into the system – sometimes by a different person than the one that recorded it in the first place. Typographical and transcription errors are common. Human error is inevitable, and once these errors become part of the data set, they become difficult to detect and eradicate, and make all the resulting reports suspect. Manually collected data is biased Whenever a human operator enters data, he or she has influence over exactly what information is entered and when it is entered. Consider the following example: Let’s say that the controller on Machine Number 1 detects an easily correctable problem and sops the machine. Let’s also say that the operator responsible for Machine Number 1 is busy elsewhere in the plant, and Machine Number 1 sits idle for an hour while the operator is otherwise occupied. When the operator is finally free, he spends 5 minutes fixing the problem, and then restarts Machine Number 1. Even though he was busy with another machine, the operator is worried that he’ll be disciplined for not attending to Machine Number 1 quickly enough, so he logs “Tooling problem – 10 minutes” as the reason for downtime.
  • 6. Automated Data Collection System Fortunately, a number of factors have combined to make automatic data collection technology much more reliable and accessible:  The emergence of high speed Ethernet as the de facto standard for local area networks has resulted in a tremendous decrease in the cost of network cards, adapters, and other hardware, thus allowing Ethernet to replace the out-dated, slow, and expensive dedicated serial networks.  It turns out that the Internet and email were not passing fads after all. Virtually all computers are now shipped with a web browser and an email client. Data collection software can now use a web browser to display and manipulate data and email to distribute reports. This has eliminated the need to install maintenance-intensive client software on workstations.  Database manufacturers adopted Structured Query Language (SQL) as a means to get data in and out of various databases. This makes it much easier for different software packages to share data, and allows an SQL-based data collection system to provide data to MES and ERP software.  It is now easier to communicate with the equipment. Microsoft and the automation suppliers got together and developed a set of standards (called OPC – described below) that allows for interoperability of different devices.
  • 7. Requirements of a good data collection system  A modern data collection system is composed of a data logger/transaction manager, a database, a report generator, and a factory viewer real-time interface. These programs typically operate together on a single server  The two “client” portions are made up of an email client (such as Microsoft Outlook) to receive reports, and a web browser (Internet Explorer, Firefox, Navigator, etc) to display the factory viewer portion.  The web browser acts as the “front end” to the system. It is used to view real time data as well as for setup and maintenance, security access, etc.  The heart of the data collection system is the data logger. The data logger is a program that gathers the raw production data, organizes it, and puts it in a database. There are two different data logging methods that can be employed by data collection systems. These are distributed data loggers and centralized data loggers.  In a distributed system, a data logger is installed on each machine. The data logger collects production data directly from the machine, stores it in memory, and periodically sends it off to the data repository (usually a database).
  • 8. Advantages and Disadvantages:  The advantage of a distributed system is that in the event of a network outage, the on-board data logger can continue to collect production information from the machine while the network is down, and then “backfill” the database when the network comes back up. However, the disadvantages of a distributed system outweigh this one advantage:  Since distributed data loggers do not continuously update the database, you cannot view the production environment in real time.  Data logging capability cannot easily be retrofitted into existing controllers. The hardware requirements for a data logger typically include multiple processors and significant on-board memory. Most existing machine controllers do not have the spare “horsepower” to run a data logger. In almost all cases, a separate dedicated (usually expensive) data logging device must be installed on each production machine.  Maintenance is more difficult with distributed systems. Inevitably, there will come a time when it will become necessary to upgrade/update the data loggers. This is usually triggered by changes in the Windows operating system. Instead of simply updating a single data logger (as you would in a centralized system) you must update every individual machine.  When it’s time for the distributed data logging devices to upload their information to the database, the resulting spike in network traffic has the potential to adversely affect your LAN.
  • 9. Data collection terminal Data collection system components
  • 10. Some of the configuration of data collection terminal that can be installed in the factory include :  One Centralized terminals  Satellite terminals  Workstation terminals The trend in industry is towards more automated factory data collection. Although they are called “automated", many of the techniques require the participation of human workers, so data collection system has included “semi-automated”.