Ultimate guide to automating quality assurance and lean manufacturing

Ultimate Guide to
Total Productive Maintenance
E B O O K
code check capture care
1300 CODING (1300 263 464) www.matthews.com

Contents
Automate your way to lean manufacturing 3
• Machine vision for quality assurance 4
• Automating your way to greater efficiency 6
• Down and dirty with data 8
• Implementing OEE measures 11
How important is TPM 15
(total productive maintenance)
to Australian manufacturers?
How Preventative Maintenance Saves 17
Money for Australian Manufacturers
What you need to know about preventive 19
maintenance vs breakdown repair
Matthews Australasia - Ultimate Guide to Total Productive Maintenance 2

Almost all industries are becoming increasingly competitive. This is particularly
true in the food and beverage industry where the traditional market shape has
altered irrevocably. The advent of private label products, the dominant role played
by the major supermarket chains, legislative requirements for product traceability,
the push for longer shelf lives without compromising product palatability or
consumer safety are just some of the issues that are adding layers of complexity
to food manufacture.
Automate your way
to lean manufacturing
The companies that are best at managing in this environment are
those that are innovative and this innovation is not limited to the
food or drink being produced.
Companies implementing continuous improvement programs
in their manufacturing processes are reaping benefits. Lean
manufacturing is actually adding to the profitability of the successful
companies.
One of the simplest and most productive ways to make your
manufacturing processes more competitive is through automation.
Having all the equipment on your line talking to each other can mean
problems are rectified in real time before backlogs and breakdowns
develop.
There is no doubt that automated online or at-line testing is a boon
for manufacturers who can see in real time when products are
moving away from their required specifications. By reacting quickly
to these variations, product loss can be minimised and raw material
consumption optimised. There is also no need for holding times
while waiting for lab clearance before releasing product. Packaging
lines can also benefit from the automation systems that are readily
available. Vision sensors can check ll levels, label placement and
orientation, missing or damaged product etc. and have out-of-spec
items removed from the line without affecting line speed.
Online, real-time quality control and system automation is now
readily and inexpensively available with the latest sensors and vision
systems. Why not look at your processes and see what you could
achieve by installing some automation?
Janette Woodhouse
Editor – What’s New in Food Technology and Manufacturing

Machine vision for quality assurance
Glenn Johnson, Editor, What’s New in Process Technology
Machine vision (MV) is the technology and techniques used in
industrial environments to provide imaging-based automatic
inspection, detection and analysis. The most common uses for
machine vision are automatic inspection and industrial robot
guidance, while in recent times, vision-based sensors for detection
purposes have become available to replace sensors such as
photoelectric sensors. Common MV applications include quality
assurance, sorting, material handling, robot guidance and optical
gauging.
Machine vision outputs
The most common output from a machine vision system is a pass/
fail decision. Such an output may in turn trigger mechanisms that
reject failed items or sound an alarm. Other common information
that can be provided by an MV system includes object position
and orientation information, which is commonly used for guidance
systems, as well as numerical measurement data, data read from
codes and characters, displays of the process or results, stored
images, alarms from automated space monitoring MV systems, and
process control signals.
General operation
The first step in the MV sequence of operation is acquisition of an
image, typically using cameras, lenses and lighting that has been
designed to provide the differentiation required by subsequent
processing. For example:
•Different types of lighting (different colours or infrared for example)
render different qualities of objects that may be of interest for
detection or inspection.
• Strobe lighting synchronised with the rate of ow of objects past the
camera allows fast snapshots to be taken of each object without
motion blur.
MV software packages then employ various digital image-
processing techniques to extract the required information and
often make decisions (such as pass/fail) based on the extracted
information.
While conventional 2D visible light imaging is most commonly used
in MV, alternatives include imaging in various infrared bands, line
scan imaging, 3D imaging of surfaces and X-ray imaging.
2D visible light imaging can be performed in monochrome or
colour, and various resolutions. The use of colour and the depth
of resolution affect the performance requirements of the image
processing hardware and software, and therefore the cost of the
solution.
The imaging device (usually a camera) can either be separate from
the main image processing unit or combined with it, in which case
the combination is generally called a smart camera or smart sensor.
When separated, the connection may be made to intermediate
hardware, such as a frame grabber, using either a standardised
(Camera Link) or custom interface. There are now also digital
cameras available that are capable of direct connections (without a
frame grabber) to a computer via FireWire, USB or gigabit ethernet
interfaces.
Processing methods
After an image is acquired it is processed. Machine vision image
processing methods include:
• Pixel counting: Counting the number of light or dark pixels.
• Thresholding: Converting an image with grey tones to simply black
and white or using separation based on a greyscale value.
• Segmentation: Partitioning a digital image into multiple segments
to simplify or change the representation of an image into
something that is more meaningful and easier to analyse.
• Blob discovery and manipulation: Inspecting an image for discrete
blobs of connected pixels (such as a black hole in a grey object) as
image landmarks. These blobs frequently represent optical targets
for machining, robotic capture or manufacturing failure.
• Pattern recognition and template matching: Finding, matching or
counting specific patterns. This may include the location of an
object that may be rotated, partially hidden by another object or
varying in size.
• Barcode, data matrix and 2D barcode reading: Reading codes for
data input or simply to check correct labelling on finished products
or shipping boxes and pallets.
• Optical character recognition: The automated reading of text such
as serial numbers.
• Gauging: The measurement of object dimensions (in pixels or
millimetres).
• Edge detection: The finding of object edges to detect their presence
and orientation.

Quality assurance applications
The main uses of vision systems for quality assurance are to
analyse images to perform appearance inspection, character
inspection, position detection and defect inspection. Some of the
main applications are:
• Detecting the presence, position and formation of a code such as a
date code or barcode
• Validating the presence and positioning of labels, such as checking
that front and back labels match the product and other elements
such as caps.
• Checking closures for tamper seals, correct caps by colour and
dimensions
• Inspecting product for ll levels, product content or other
parameters
• Sorting products based on marking
Advantages for quality
assurance
The major benefits of machine vision inspection solutions are:
• Cost savings due to reduced rework, more reliable product quality
and less wasted product
• Automation of quality to provide more objective QA compared with
manual inspection
• Greater transparency throughout the inspection process and
improved process control
• Real-time quality metrics can be made available for OEE data
Examples of QA applications
Code validation
Machine vision solutions for code inspection are used to verify code
presence, position and formation, and sometimes to also provide
code reading and matching. Such systems can also automatically
identify and reject containers or packages with missing, incorrect or
unreadable codes to ensure only properly coded items are produced.
Examples of the use of code validation are the validation of date
codes, batch codes, barcodes and 2D data matrix codes.
Date code verification verifies that a code is present and is
completely formed in the correct location, while batch code
verification checks the quality of the printed batch information,
ensuring it cannot be misread, possibly resulting in product recalls.
Barcode verification checks that barcodes are readable and correct,
helping to ensure correct product tracking through the supply
chain. 2D data matrix validation verifies that information which
is not human readable is still valid, and is properly decoded and
understood by the quality system.
Label inspection and validation
High-speed labelling of products, of all types, shapes and sizes, can
result in a wide variety of possible defects. These defects can lead
to label errors that can be harmful to a brand or even present liability
issues for a brand owner. Labels can be inspected for label presence,
wrinkles, tears, skewed labels, double labels, flagged or missing
labels, as well as incorrect label pairs on containers and packages.
Machine vision technology for label inspection can be set up to help
ensure perfect product presentation and correct labelling. Packages
and containers with incorrect or defective labelling can then be
automatically rejected in the production line.
Label presence and pairing can be checked, both to ensure labels are
present and also that front and back labels are paired correctly with
each other.
Skewed and dog-eared label detection ensures that labels are
applied correctly and straight, and in the correct position, while
double label inspection can make sure that only one label has been
applied to the same location on the package.
Overwrap alignment is another form of label inspection in which
wraparound labels are checked for straightness and proper position.
With appropriate MV system design, a 360-degree inspection on
round bottles can be performed.
Confirming that the correct label has been applied is often performed
using graphical label verification (in which a unique graphical item on
the label is used to confirm that the proper label has been applied)
or by using 2D data matrix code verification where 2D dm codes are
being used on the labels. Similarly, barcode verification: confirms
that the proper label has been applied by verifying that the correct
barcode is present.
Closure and seal validation
Obviously the integrity of closures and seals on bottles and other
containers is important for the quality of the product and the safety
of the consumer. MV systems can be used to visually check the
closures and seals for integrity.
Checking the closure’s colour and dimensions verifies that the right
closure has been applied to the container, while visually checking
liner formation and placement ensures the product is properly sealed
and protected from contamination and leakage. In the same way,
tamper seals can be checked to make sure they are not broken.
Packaging and filling
Machine vision systems can inspect filled bottles, trays, pouches,
cases, cartons and other packages to verify that the packaging
process was completed to the specifications required.
Bottles can be inspected to ensure that they are properly filled,
labelled and capped to minimise product spoilage and ensure
perfect product presentation, and case quality inspection can also be
performed to verify that cases are properly sealed and undamaged,
to allow fast and reliable palletising and packing.
MV technology can also be used to check the content of products
made of discrete items, confirming that the specified contents are
present, thereby demonstrating due diligence and reducing the costs
associated with missing or additional components, parts or other
items.
As published on www.foodprocessing.com.au

Automating your way to
greater efficiency
Modern control and automation systems which combine management and
production levels are helping companies automate their way to success.
The simplest change to a production line, even just an operating
system update, can cause havoc, since the slightest change can
impact the entire operation. However, by
having an intelligent link between the products being manufactured,
the facilities doing the manufacturing and the IT systems
controlling things, factories can be automated to react more or less
autonomously to any changes.
The key thing is to put in place intelligent links between the
manufacturing facilities and the IT systems.
Often if a product is changed, the first step is to rearrange the
production line. Only then is the IT system reconfigured. What’s
more, the details of each machine that belongs on the line have to
be entered manually into a computer. This work is tedious, time-
consuming and error-prone. And frequently mistakes are only
identified when the line is back up and running.
These conventional ‘island’ solutions, based on manual processes,
do not provide a cost-efficient way to manage a food or beverage
plant where batch tracing, cost pressure and sustainability - along
with the product consistency and diversity demanded by the
customer - have to be facilitated.
Managing, controlling,
monitoring, visualising and
analysing
Modern production control systems manage, guide, monitor and
visualise the entire production process. Ideally, the operator can see
on the screen at a single glance whether the production processes
are running as they should. The control systems also log, analyse,
compress and archive a range of data from the process chain from
delivery of raw materials through to the completed, packaged end
product.
On the one hand this secures the legal requirement for batch tracing.
And on the other, the production ﬁgures thus acquired enable the
company to conduct a detailed analysis of the processes.
Production control systems can also pass on data to the higher-
level ERP (enterprise resource planning) system, which integrates
planning and commercial functions. In this case the company
management and production levels are then combined in a single
transparent data platform.
Operators, technicians, operational managers, controllers and
executive managers all have access to the information they require
in order to make quantitative and qualitative statements about the
current situation. And they have this access at a glance, and in real
time, regardless of company size.
From cables to networks
The heart of an automated control system is the programmable logic
controller (PLC). This is connected to the machine or system via
sensors or actuators that are linked to the PLC inputs and monitor
the processing stages.
Examples of sensors are temperature sensors, light barriers and
limit stop switches. The actuators in turn are connected to the
PLC to control the machine or system. Examples of actuators are
contractors to switch on electric motors or electric valves.
Traditionally, in the field level, the signals are exchanged between
sensors, actuators and control modules via parallel lines.
Increasingly, however, fieldbus systems are being used to permit
digital communication between the automation unit and the
field devices via a single serial line. Accordingly, this reduces the
requirement for cabling and input/output hardware, which brings
significant cost savings.
The connection to higher-level control and management levels is
represented via networks such as ethernet. Wireless communication
systems such as WLAN make it possible, using a hand scanner, to
scan product data on incoming goods, feeding the information into
the production control system that follows these goods through the
entire manufacturing system.

Benefits of ‘smart’ systems
‘Smart’ systems don’t want holidays, never get sick, don’t ask for
pay rises and keep working 24 hours a day with minimal human
intervention. Machine-to- machine (M2M) communication reduces
the likelihood of human error as it is based on automated wired or
wireless communication between mechanical or electronic devices.
This allows networked machines to exchange information and
perform actions without human assistance.
Physical conditions that can be monitored include temperature, fluid
leaks, energy spikes, location, consumption, heart rate, stress levels,
oxygen levels, light, movement, altitude, speed and many more.
Wireless carriers have partnered with service delivery platform
providers to make their networks more accessible to M2M
applications. Globally connected solutions can be created using
wireless communications such as GSM, CDMA and satellites. Some
of these connections occur over a relatively short range, some over
many kilometres.
When looking at the advantages and disadvantages of wireless
M2M applications, it is important to consider how the design factors
of the data link can play a most important role in terms of real-
time guarantees, energy efficiency, scalability, throughput, latency
and reliability. Such varied design implications have increased the
complexity of finding the ideal balanced and cost-effective solution
across a wide range of diverse applications.
In the past, the effective polling, monitoring, storing and fusing
of vast quantities of data coming from hundreds and sometimes
thousands of network devices have been challenging. Now, with
smarter devices, software and more reliable networks, new M2M
applications are possible and reliable. The widespread availability
and decreasing cost of wireless communication is making M2M
applications more cost-effective to implement.
The key components of an M2M system are sensors, RFID, a Wi-Fi
or cellular communications link and autonomic computing software
programmed to interpret data and make decisions while remaining
transparent to the user.
The most well-known type of M2M communication is telemetry,
which has been used since the early part of last century to transmit
operational data. Pioneers in telemetrics first used telephone lines
- and later radio - to transmit performance measurements gathered
from monitoring instruments in remote locations.
Currently, M2M does not have a standardised connected device
platform and many M2M systems are built to be task- or device-
specific. It is expected that as M2M becomes more pervasive,
vendors will need to agree on standards for device-to-device
communications.
The OPC Foundation is using the fundamental standards and
technologies in the general computing market to adapt and create
specifications that ll industry-specific needs.
OPC is all about open productivity and connectivity in industrial
automation and the enterprise systems that support industry.
Interoperability is assured through the creation and maintenance of
open standards specifications. There are currently seven standards
specifications completed or in development.
The rst standard (originally called simply the OPC Specification
and now called the Data Access Specification) resulted from
the collaboration of a number of leading worldwide automation
suppliers working in cooperation with Microsoft. Originally based
on Microsoft’s OLE COM (component object model) and DCOM
(distributed component object model) technologies, the specification
defined a standard set of objects, interfaces and methods for use
in process control and manufacturing automation applications to
facilitate interoperability. The COM/ DCOM technologies provided
the framework for software products to be developed. There are now
hundreds of OPC Data Access servers and clients.
Automatic production
processes mean automatic
measurements
Full automation of production processes also has another facet:
if you automate your production processes, then you can also
automate your quality control.
By moving away from labour-intensive sampling and time-delayed
analysis in the decentralised laboratory towards inline measurement,
large improvements in productivity and efficiency can be achieved.
Not only are sensors available for measuring physical parameters
such as ow and pressure, but also the parameters necessary for
quality control; for instance pH, conductance, original wort, brix,
turbidity, CO2 and O2 can all provide information in real time and
even recognise trends and trigger corrective actions before the
product goes out of specification.
With inline measurements and inline sampling you remove the two
biggest risk factors in quality control - the human being and the
statistically inconclusive random sample. And it’s all done without
interrupting the production processes, without significant product
losses and, not least, without spending too much time or personnel
input. All of which result in real economic advantages.
Even microbiological issues - so very important in the food sector -
can be addressed using a sterile inline sampling system.
Smart systems are not prohibitively expensive and with wireless
communications they do not have to be hard wired, so installation is
also simple, flexible and affordable.

Down and dirty
with data
Significant manufacturing and business efficiency gains are possible by
implementing automated systems but they won’t be achievable unless the data
they depend on is accurate and reliable.
Last year the GS1 Australia Data Crunch Report revealed that
retailers are working with data that is inconsistent more than 80%
of the time. And, over the next five years, Australian grocery retailers
and suppliers are expected to experience over AU$350 million in
profit erosion and AU$675 million in lost sales as a result of bad
data. The total cost of bad data in the Australian grocery supply
chain will be AU$1.035 billion over five years.
In the study, researchers compared data on grocery products
held by three major supermarket retailers (Woolworths, Coles and
Metcash) and matched this against product data from four major
suppliers (Kimberly-Clark, Nestlé, Procter Gamble and Unilever). It
was prepared in conjunction with IBM and highlights the impact of
bad data on profits and consumer service in the Australian grocery
industry.
The study also showed that retailers and sup-pliers using data
synchronisation through GS1net had significantly better data quality
results than those who did not (fully) adopt data synchronisation.
GS1net lets manufacturers and suppliers enter, validate, store and
maintain product, pricing and other related trade information in a
single location so it can be shared with their trading partners.
Achieving global data
synchronisation
GS1 Australia and Nestlé Australia have trialled a Global Data
Synchronisation (GDS)-based process which enabled Nestlé
Australia to make its extended product data available to consumers
on the new GS1 GoScan iPhone application that is launching in late
2012.
Incorporating the GS1 Global Data Synchronisation Network*
(GDSN), the local GS1 data pools in Australia and the United States,
plus Nestlé Australia’s own databank in Australia, the end-to-end
process is an example of GDS working seamlessly around the
world to deliver trusted, high-quality and extensive product data to
consumers, on demand.
Mark Fuller, Chief Operating Officer at GS1 Australia, says this is a
world first for GS1 using GDSN for the benefit of consumers.
“To date, efforts in this space have been only pilots. Our project with
Nestlé Australia is a significant milestone that demonstrates how
advanced the GS1 GDS system is and how it can work at its best to
enable us to advance and deliver trusted data to consumers,” Fuller
said.
Driving this project was Nestlé Australia’s goal to make its extended
product information available on the new GS1 GoScan application.
GS1 GoScan is the first whole-of-industry endorsed application to
deliver trusted extended product information to consumers, direct
from the brand owners.
For Nestlé Australia, this data includes nutritional and ingredient
information, allergen declarations and other consumer advice,
dietary information and much more.
Nestlé Australia has been part of the GS1 GoScan project from
the beginning, assisting GS1 Australia with the development of
the application alongside industry associations, national health
organisations, universities, major retailers, and other local and global
food manufacturers.
“It’s a huge accomplishment to see our product data appear on the
GS1 GoScan app. It adds a new dimension to how we communicate
with consumers and ensure they always have the most accurate and
up-to-date information at their fingertips,” said Mandeep Sodhi, B2B
Supply Chain Technology Manager, Nestlé Australia.
“Because we are a global company and our product information is
held in various databanks around the world, the process was more
complex,” Sodhi said.
Nestlé Australia’s product data is managed and maintained in SAP
and Nutribank. Nutribank is an Australian database designed to
assist the organisation manage detailed product composition and
formulation data, such as ingredient lists, nutritional information,
allergen declarations and other key product data. Nutribank data is
integrated into Nestlé’s global master data management platform.

Data is automatically loaded as part of Nestlé’s existing GDS
processes into 1SYNC**, the GS1 US data pool, from where it travels
back to Australia to GS1net - GS1 Australia’s data synchronisation
data pool.
The data is validated for completeness and accuracy during Nestlé’s
label approval process and also when it is loaded onto GS1net,
and then processed through to GS1 GoScan’s database where it
becomes available to consumers via the iPhone application.
“These systems and standards that form the foundation of GS1
GoScan have been used by the Australian industry for more than
14 years. GS1net is used by food, grocery, liquor and healthcare
suppliers to share master product data with trading partners,
retailers, government agencies and now consumers. More than
500,000 product records from almost 1400 suppliers are available on
GS1net today,” Fuller said.
Sodhi said working with GS1 Australia on this project has enabled
Nestlé to further realise the benefits data synchronisation can bring
to the organisation.
“With so many elements involved, we wouldn’t have been able to
achieve this result without the GS1 GDS standards, the support from
1SYNC and the dedicated work of the Nestlé, Nutribank and GS1
teams in Australia, and the Nestlé head office in Switzerland,” he
said.
“At Nestlé, good data is of great importance to us and is critical to
the reputation of our brand and our products. From the start, we
have been deeply committed to working with GS1 Australia to make
GS1 GoScan a reality.”
Dan Wilkinson, Vice President, 1SYNC said, “Nestlé’s industry
leadership in this effort will help others see the value in leveraging
the GDSN for tangible business benefits. We’re honoured to sup-
port Nestlé in achieving this important milestone and ultimately
helping them leverage product data to maintain their exceptional
brand reputation.”
GS1 GoScan is expected to be launched in October 2012. GS1
Australia continues to work with brand owners to upload their data
for use in GS1 GoScan and invites companies to participate for the
benefit of consumers.
Automatic identification and
data capture
Before you can synchronise your data you have to collect it.
Automatic identification and data capture (AIDC) is a broad category
of technologies used to collect information without manual data
entry. AIDC systems can be used to manage inventory, delivery,
assets, security and documents.
AIDC applications typically fall into one of a few categories:
identification and validation at the source, tracking and interfaces
to other systems. The actual technologies involved, the information
obtained and the purpose of collection vary widely.
In the majority of cases, AIDC systems work without any human
involvement. Where human involvement is required, this is normally
confined to a user scanning an AIDC-equipped item (such as a can
of food which is barcoded or an RFID- equipped door entry pass).
AIDC has advanced greatly over the years and it is now possible
for users around the world to interact with millions of business
processes and systems using AIDC-equipped electronic devices.
Despite this, there is still room for improvement in supply chain
visibility and development of internal business processes.
Current AIDC technologies
Barcodes
Since the invention of barcodes over 50 years ago, they have been
widely used and are key to accurate data capture and facilitating the
rapid movement of goods, and all types of automation.
Now, not only are there the well-known 1D barcodes and 2D
barcodes, but 3D barcodes also exist. Unlike 1D and 2D barcodes,
the bars in a 3D barcode are read by a scanner that reads the
differences in the height of each line. Other types of barcodes are
read by the variances in reflected light as the light scans the code.
The 3D barcode scanner uses a laser that calculates the height of
the barcode’s lines based on the distance and time it takes for the
laser to read it.
The labelling of items with 3D barcodes is called direct part
marketing (DPM) and is used in situations where 1D and 2D
barcodes are unsuitable. Limitations caused by high temperatures,
chemicals and solvents that would easily destroy a barcode printed
on paper or a sticker can be overcome with 3D barcodes.
Barcodes in common use are covered by international standards
which include:
• Rules for representing data in an optically readable format,
• Rules and techniques for printing or marking,
• Reading and decoding techniques, and
• Rules for measuring the quality of printed/marked symbols.
Radio frequency identification
Radio frequency identification (RFID) is a technology that uses
radio waves to transfer data between a reader and an electronic tag
which is attached to a particular object. Typical uses are for object
identification and tracking.
The use of RFID technology will, no doubt, continue to multiply as
the use of barcodes has since their introduction over 40 years ago.
The major advantage of using RFID tags is that multiple RFID tags
can be read at the same time, and they do not have to be visible,
unlike barcodes which can only be read one at a time and need to be
placed on the outside of items to be scanned.
Most RFID tags contain two parts: firstly, a circuit which stores and
processes information and the other, an antenna for receiving and
transmitting the signal.
Typically, two types of RFID tags are available: RFID tags which
need to have a power source (active RFID tag) and RFID tags which
do not need to have a power source (passive RFID tag) as they are
powered by the RFID reader, at the time that the RFID reader reads
the information from it.
Optical character recognition
Optical character recognition (OCR) is the electronic translation of
scanned images typically handwritten, typewritten or printed text
into machine-encoded text. This technique is often used to convert
books or documents into electronic files, perhaps to computerise a
record-keeping system or to publish the text on a website.
OCR makes it possible to edit the text, search for a word or phrase
and store it more compactly. Further techniques can then be applied
such as translation or text-to-speech recognition.

Smart cards
A smart card is typically a pocket-sized card that has a small
chip attached which contains an integrated circuit. There are two
categories of smart cards: memory smart cards, which contain non-
volatile memory, and microprocessor smart cards, which contain
volatile memory together with microprocessor components.
Smart cards are capable of providing identification, authentication,
data storage and application processing. They are typically made of
plastic and may be used to provide strong security authentication for
single sign-on systems within large organisations.
The benefits of smart cards are directly related to the volume of
information and applications that are programmed for use on a card.
Voice recognition
Voice recognition (or speech recognition) converts the spoken words
to text. Voice recognition may also be used to refer to recognition
systems that have been trained to a particular speaker. This is the
case for most desktop (computer) recognition software - once the
speaker has been recognised, it is simply a task of translating the
spoken words of that particular person.
Speech recognition is a much broader classification and refers to
technology that can recognise speech without being targeted at a
certain speaker.
Speech recognition applications include voice user interfaces such
as voice dialling, call routing, domestic appliance control, search,
simple data entry, preparation of documents, speech-to-text
processing.
Electronic article surveillance
Electronic article surveillance (EAS) is a technology used to identify
items as they pass through a gated area. Typically, this identification
is used to alert someone of the unauthorised removal of items from
a store, library or data centre.
The underlying technology used in EAS is RFID and there are several
types of EAS systems. In each case an EAS tag or label is affixed to
an item. If the tag has not been deactivated before it passes through
a gate an alarm sounds.
Often these days, an EAS tag is placed in the product at the time
of manufacture or packaging, which makes the labelling of goods
unnecessary (in the store), saving time and money.
Real- time locating systems
Real-time locating systems (RTLSs) are typically fully automated
systems that continually monitor the positions of objects and
personnel.
An RTLS will often use battery-operated RFID tags and a mobile
network-based locating system to detect the location and presence
of the tags. The locating system will usually be deployed as a matrix
of locating devices installed at a spacing of anywhere from 15 to 300
m. These locating devices determine the locations of the RFID tags.
RTLSs continually update a central database with current RFID tag
locations at a predefined time setting.
Magnetic strips
A magnetic strip, typically found on a magnetic stripe card, is
capable of storing data by modifying the magnetism of small
iron-based magnetic particles on a strip of magnetic material. The
magnetic stripe, sometimes called a swipe card, is read by physical
contact and swiping past a magnetic reading head.
A number of international organisation standards (including ISO/
IEC 7810, ISO/IEC 7811, ISO/IEC 7812, ISO/IEC 7813, ISO 8583, and
ISO/IEC 4909) define the physical properties of the card, including
size, flexibility and location of the magnetic strip, its magnetic
characteristics and data formats.
Typical magnetic strip usages are for access control, ID cards and
key cards (used to operate locks and storing a physical or digital
signature which the door mechanism accepts before opening the
lock, sometimes also containing an RFID proximity tag).
Biometrics
Biometrics is typically involved in establishing people’s identities
using a biometric template of the individual.
Biometric systems can work under two modes: biometric verification
and biometric identification. In the former, a one-to-one comparison
of a captured biometric with a stored template is used to verify
identity. Whereas in the latter, the captured biometric is compared
against a database in an attempt to identify a known or unknown
individual.
The first time an individual uses a biometric system they have to
enrol, during which time biometric information from the individual is
stored.
Typical biometric systems include fingerprint recognition, face
recognition, palm print recognition and iris recognition (which has, in
the main, replaced retinal recognition).
*The Global Data Synchronisation Network
enables companies to connect and
communicate with their trading partners and
improve the accuracy and efficiency of their
collaboration. Using GS1 GDSN-certified data
pools such as GS1net and 1SYNC, companies
register and synchronise supply-chain
information through the GS1 Global Registry,
which serves as a centralised information
directory. The elimination of informational
inaccuracies helps companies achieve a
wide range of business benefits, including
reductions in out-of-stocks, incorrect
deliveries, purchase order/ invoicing errors and
transportation costs.
**1SYNC, the largest certified data pool in
the Global Data Synchronisation Network, is
dedicated to the implementation of standards-
based, global supply chain solutions. 1SYNC
offers a robust, easy-to-use solution that can
reduce costly data errors and increase supply
chain efficiencies for companies of all sizes.
The growing 1SYNC community consists of
60 leading recipients and more than 7000
suppliers worldwide. These customers are
synchronising product data on more than six
million items in the GDSN.

Implementing OEE measures
In the packaging hall to achieve operational excellence
Executive summary
On average, plants waste up to 40% of their capacity through stops,
speed losses, interruptions and defects - yet managers often don’t
know the reasons causing the downtime. Nor do they know the
factory’s true performance, or how to improve it.
Implementing overall equipment effectiveness (OEE) measurement
tools gives a much clear understanding of where improvements
can be made. OEE is a globally recognised best practice measure to
systematically improve processes for higher efficiencies and better
productivity - ultimately leading to lower manufacturing costs and
higher profitability.
This application paper examines OEE metrics and how to capture
them. Not only must this data be captured, but performance
data needs to be available in real time to everyone: operators,
maintenance personnel, supervisors and managers.
iDSnet Manager provides an overall framework for capturing data
that can feed into overall OEE metrics. iDSnet Manager can also
feed data to production floor scoreboards for visual OEE and to the
production office in the form of live dashboard reports. These reports
show in-depth, real-time production-line performance monitoring,
giving actual production efficiencies, including idle times and
breakdowns, plus reporting on what’s causing production stoppages.
What is OEE?
OEE - or overall equipment effectiveness - is a global best practice
measure to monitor and improve the effectiveness of manufacturing
processes (that is, machines, packaging halls, assembly lines, and
so on).
OEE is frequently used as a key metric in TPM (total productive
maintenance) and lean manufacturing programs to deliver
operational excellence. It gives manufacturers a consistent way to
measure the effectiveness of TPM, and other initiatives (‘six sigma’
and ‘world-class manufacturing’), by providing an overall framework
for measuring production efficiency.
OEE takes into account three factors:
1. Quality
2. Speed
3. Downtime
It is simply the ratio of fully productive time to
planned production time. In other words, it rep- resents the
percentage of production time spent making good pieces (no quality
loss), as fast as possible (no speed loss), without interruption (no
downtime loss).
OEE benchmarks
As a benchmark, what is considered a ‘good’ OEE score?
• An OEE score of 100% is perfect production: manufacturing only
good parts, as fast as possible, with no downtime.
• An OEE score of 85% is considered world-class for discrete
manufacturers. For many companies, it is a suitable long-term
goal.
• An OEE score of 60% is fairly typical for discrete manufacturers, but
indicates there is substantial room for improvement.
• An OEE score of 40% is not at all uncommon for manufacturing
companies that are just beginning to track and improve their
manufacturing performance. It is a low score and, in most cases,
can be easily improved through straight-forward measures (eg, by
tracking downtime reasons and addressing the largest sources of
downtime - one at a time).
Industry speciﬁc OEE bechmarks
80%
70%
60%
50%
40%
30%
20%
10%
0%
Food Beverage
Food Beverage
CPG
CPG
100% (Perfect) 85% (World Class)
Industrial
Pharmaceutical
Pharmaceutical
Best in Class
77.7%
82%
89.9%
45.2%
Middle 50%
61.7%
54.9%
55.5%
30.8%
Laggards
42.4%
29.9%
41.8%
23.5%
Waste OEE
60% (Typical) 40% (Low)
Source: http://www.informance.com/benchmarks/
80%
70%
60%
50%
40%
30%
20%
10%
0%
Food Beverage
Food Beverage
CPG
CPG
Industrial
Pharmaceutical
Pharmaceutical
Best in Class
77.7%
82%
89.9%
45.2%
Middle 50%
61.7%
54.9%
55.5%
30.8%
Laggards
42.4%
29.9%
41.8%
23.5%
Waste OEE
Benchmark your OEE score against industry standards for discrete
manufacturing and strive for world-class results.
Source: http://www.leanproduction.com/oee.html
80%
70%
60%
50%
40%
30%
20%
10%
0%
Food Beverage
Food Beverage
CPG
CPG
Industrial
Pharmaceutical
Pharmaceutical
Best in Class
77.7%
82%
89.9%
45.2%
Middle 50%
61.7%
54.9%
55.5%
30.8%
Laggards
42.4%
29.9%
41.8%
23.5%
Waste OEE

Why should you
measure OEE?
“You cannot manage what you cannot measure.” - Bill Hewlett, Co-
founder of Hewlett-Packard
With global organisations looking to achieve higher manufacturing
efficiencies by consolidating operations and encouraging lean
manufacturing, measurement has become critical because the
operation’s survival depends on the success of these programs.
Even the most basic manufacturing operation is extraordinarily
complicated. Factories have thousands, perhaps millions, of
variables moving around at the same time. Just about every event
has multiple drivers. Actions taken to optimise one variable often
come at the expense of another. Performance metrics at the activity
level can be traded off against other performance measures. Labour
efficiency can be increased to the detriment of quality; machine
utilisation can be maximised in the short term to the detriment of
machine life; delivery performance can be increased to the detriment
of inventory levels and overhead expenses ... and so on.
Management cannot possibly measure thousands of variables with
equal attention and diligence. When one or two are elevated to the
top - and treated as overall process outcome metrics rather than
event metrics - then the motivation to optimise those few variables
is created. However, this is usually to the detriment of variables that
are not elevated to high-level status.
Your performance measurement system should:
• Provide timely feedback to determine the operation’s successes,
• Determine improvement areas, and enable quick decision-making.
OEE measurement does just that.
How can you measure OEE?
The industry-standard OEE metric is defined as follows: Availability x
Performance x Quality and is designed to quantify stoppages, speed
losses and wastage.
The diagram below shows the required measurements to enable the
OEE calculation.
Plant Operating Time: is the amount of time the facility is open and
available for equipment operation.
Planned Machine Production Time: is the amount of time you
intend to run production (plant operating time minus breaks, lunch,
scheduled maintenance, or periods where there is nothing to
produce).
Actual Running Time: the amount of time the plant or line actually
runs (planned machine production time minus stoppages).
Stoppages (breakdowns, set-up and adjustments): these include
any unplanned downtime, such as equipment failures, breakdowns,
material shortages, changeover time, adjustment time, warm-up
time and so on.
The above iDSnet Manager dashboard provides production
efficiency, performance, planned downtime, unplanned downtime
as well as no run time. (Panned D/T: 7.3%; Unplanned D/T: 28.8%;
No Run: 3.9%; Production: 60%; Performance: 132%)
The above iDSnet Manager dashboard provides information on causes
of unplanned downtime assigned by the operators via reason codes.
Plant Operating Time
A - Planned Machine Production Time Planned Plant Shutdown
B - Actual Running Time Stoppages
C - Machine Production Rate
D - Actual Production Rate Speed Loss
E - Places Produced
F - Good Parts Wastage
OEE = Availablity (B/A) X Performance (D/C) X Quality (F/E)
Availability =
Actual Running Time
Planned Machine Production Time
Performance =
Actual Production Rate
Machine Production Rate

Machine Production Rate: is the plant’s stated potential, or
Ideal Cycle Time, being the theoretical fastest possible time to
manufacture one piece. When multiplied by Total Pieces, the result
is Net Operating Time - the theoretical fastest possible time to
manufacture the total quantity of pieces.
Actual Production Rate: is the actual time that the plant or line is
producing goods.
Speed Loss (small stops and reduced speed): this includes loss
due to obstructed product flow, rough running, under nameplate
capacity, under design capacity, machine wear, substandard materials,
misfeeds, cleaning, checking and operator inefficiency.
Pieces Produced: is the total number of goods produced.
Good Parts: is the total number of ‘good’ items produced (without
rework) that can be shipped to the customer.
Wastage: goods that need to be re-run, need rework, received in-
process damage, expired in process, were assembled incorrectly and
so on.
Quality takes into account Quality Loss, which accounts for produced
pieces that do not meet quality standards, including those needing
rework.
The remaining time is called Fully Productive Time.
Out of all the above metrics, Quality is probably the hardest to measure
and quantify. This is only because product is often re-run while on the
line and therefore small wastage is hard to measure, as opposed to an
entire batch being re-run, which is far more likely to be captured.
Rejects that are scrapped and not re-run is real Wastage.
The goal is to maximise Fully Productive Time.
This chart includes a bar chart showing the Production Count for
each timeblock across the selected period split into Good Count
and Reject Count (via iQVision system).
Clicking on one of the Reject sections of the Quality Analysis chart
above expands it to show a breakdown by each Reject code.
Quality =
Good Parts
Pieces Produced
How can iDSnet Enterprise
and Manager capture OEE
measures?
iDSnet Enterprise captures data from all coding and labelling
machines, as well as all other end- of-line equipment such as
vision systems and scanners, and has the potential to collect data
from other packaging equipment on the production line. iDSnet
thus has a count of every primary product, every carton and pallet
via the network, while vision systems and scanners help capture
the measurement’s quality aspect. Vision inspection checks
elements like code presence, label position, tamper seals, label
match, barcodes and so on, to ensure that the product is shelf
ready. They can also verify that cartons have the right number of
products, if orientation of products is correct, etc. Scanners check
if all barcodes are scannable, hence avoid products being rejected
by the customer (or distribution centre).
Target run rates are easily set up in iDSnet Manager, hence it is
easy to track production in real time versus the targets.
Measuring ‘downtime’ not
enough
It is not only important to know how much unplanned downtime
your process is experiencing (and when), but also to be able to
attribute the lost time to the specific source or reason for the loss
(tabulated through reason codes). With downtime and reason-
code data tabulated, root-cause analysis can be done, beginning
with the most severe loss categories. iDSnet Manager allows the
operators on the line to immediately select and put in fault codes/
reason codes easily to assign the unplanned downtime, which
ultimately helps in analysing the root cause.
Micro stoppages and reduced speed are the most difficult
to monitor and record. iDSnet automatically records them.
Companies can set parameters of what a micro stoppage is
and what needs to be accounted for with reason codes that the
operators can easily enter via a communication interface module
(CIM) on the production line.
Eliminating unplanned downtime is critical to improving OEE: other
OEE factors cannot be addressed if the process is down.
Tracking set-up time is critical to reducing loss, together with
an active program to reduce this time. By networking all coding,
labelling and other devices back to a central database, product
changeovers are effected down an entire production line with one
simple operator action - thus reducing set-up time.
iDSnet can differentiate start-up rejects and production rejects via
reason codes, since often the root causes are different between
initial and steady state production. Parts needing rework of any
kind should be considered rejects and can easily be picked up by
scanners or vision systems. Tracking when rejects occur during
a shift and/or job run can help pinpoint potential causes and, in
many cases, patterns will be discovered.
Categorising data makes reject analysis much easier. A key goal
should be fast and efficient data collection, with data put to use
throughout the day and in real time. This is exactly what iDSnet is
designed to do.
Acceptable tolerance levels can be set up in the system, and if the
reject rates go over the limit, an alarm can be raised or the line
can be stopped. This gives operators the ability to take immediate
action when there is a major quality issue, such as the wrong label
roll has been loaded, so all products have the wrong label.
iDSnet Manager helps in the realm of ‘Continuous Improvement’,
and aids the faster flow of value by providing greater visibility of
production data and product flow in the packaging hall in real time
through OEE metrics, charts and reports.

Scoreboards
iDSnet Manager produces live dashboards, with in-depth, real-time
production-line performance monitoring. It gives actual production
efficiencies, including idle times and breakdowns, plus detailed
reports on what’s causing production stoppages.
Along with these reports, iDSnet Manager connects with shop
floor scoreboards for visual OEE. This real-time information makes
operators and line supervisors instantly aware of current production
efficiencies against known targets, as well as alerting them to issues,
allowing the operators or managers to quickly address the issues
and avoid any significant productivity losses.
The scoreboards are set up such that the data in green means set
targets are being met, orange de- notes warning while red data
reflects that performance is below targets.
This can be used to encourage competitiveness between lines and
shifts leading to better performance from the shop floor.
Summary
Unplanned factory downtime impinges on profit. Measuring
‘downtime’ is a beginning, but to really improve productivity, the
plant must understand the reasons for each and every occurrence.
Implementing OEE gives everyone in the factory a much clearer
understanding of where these improvements can be made. iDSnet
collects and analyses data quickly and efficiently, putting it to use
throughout the day and in real time.
iDSnet Manager does this by providing real- time reports and
dashboards, as well as storing the data for historical analysis.
The customised, web-based dashboards and reports give plant
managers visibility and insight into production efficiencies, by date,
by line and so on.
iDSnet Manager:
• Provides real-time feedback to enable quick decision-making,
• Highlights improvement areas, and determines the operation’s
successes.
It gives operators and managers the ability to take immediate action
to reduce downtime, as well as the confidence to make long-term
strategic decisions to improve productivity based on the historical
data by eliminating unplanned downtime.
References
http://www.foodprocessing.com.au/articles/37353-
Overallequipment-effectiveness
http://www.aprc.com/tpmover.htm
http://www.matthews.com.au/Solutions/Our-Tech- nology/Real-
time-PerformanceMonitoring/iDSnet- Manager/Manager
http://www.lean.org.au/what-is-lean
http://synoptic.com.au/Lean%20Article.pdf
http://www.leanproduction.com/oee.html
http://en.wikipedia.org/wiki/Overall_equipment_ef- fectiveness
http://www.makigami.info/cms/overall-equipmentef- fectiveness-oee
http://blog.gcase.org/2011/05/25/what-are-perfor- mancemetrics/
http://www.informance.com/benchmarks/
http://www.bukisa.com/articles/361488_top-tenman- agement-on-
corporate-objectives-an-overview-of- howto-get-an-organization-to-
perform-at-its-full- potential-anddeliver-the-best-results
http://www.infoentrepreneurs.org/en/guides/meas- ureperformance-
and-set-targets/
time-Performance-Monitoring/iDSnet- Enterprise/iDSnet-Enterprise-
Solution
time-Performance-Monitoring/iDSnet- Manager/Manager
http://www.matthews.com.au/Solutions/Our-Technol- ogy/Vision-
Systems
http://www.iqvision.com.au

In Japan, Toyota showed that to maximise the money you can make in
manufacturing, you need Total Productive Maintenance (TPM). In other words, you
have to take care of your equipment so you can eliminate all unplanned downtime.
It means you need highly trained operators to do two things all the time on your equipment: fault-find and basic maintenance. Getting production
equipment to work perfectly is a key component of Overall Equipment Effectiveness (OEE).
But how closely does the average Australian manufacturer have to listen to the discoveries of a large international automaker?
Sure, TPM (or, if you like, Total Productive Maintenance) generated more profit for Toyota but at what point does the benefit of having preventative
maintenance outweigh the expense of setting up Total Preventative Maintenance on the line? Let’s examine two approaches to equipment
management: Reactive Maintenance vs. Preventative Maintenance.
How important is TPM
(total productive maintenance)
to Australian manufacturers?code check capture care

The traditional approach:
reactive maintenance
Potential Benefits: Hopefully, your equipment won’t break down.
Even better, if it does break, an inexpensive, quick-stop solution
may hold. With some luck, you won’t have to spend much money
on repairs, parts, tools, or maintenance labour. Cross the bridge of
“downtime” and idle labourers when you come to it.
The Costs: Reacting to maintenance on an “as needed” occurrence
has the attractiveness of flexibility. Until you find yourself in a rut—
unable to get the parts or labourers you need within a profitable
timeframe.
The “putting out fires” approach usually occupies valuable resources,
as key staff or technicians are forced to make crisis management
time in their day.
Worse, when you do have to fix something, you are working on
limited information. You’ll have to order supplies, tools, and trained
labourers when breakdown happens, leading to unpredictable
downtimes. And all the while your floor staff are idle, unable to do
their jobs.
If products aren’t going out, and you’re unable to meet your
commitments, reactive maintenance to a breakdown on the line
could cost you more than is necessary in money, and sales, and
customer relationships.
The lean approach: predictive,
preventative maintenance
Potential benefits: On a closely monitored line, you have more
information about the condition of your equipment. So you can
discover what’s causing the breakdowns or production stoppages
more quickly.
You’ll avoid the “grey” areas of assessment (and dodge unnecessary
equipment purchases) with up-to-date, real-time information
on hand. It also means you can get to the root cause of quality
problems by ensuring equipment competence. When your product is
coming off the line with first-pass quality assurance, you avoid the
expense and hassle of rework.
Preventative maintenance is also a major factor in increasing the
life of your line equipment. In fact, many Matthews customers have
deployed assets in the field for 10 (or more) years—even though the
expected financial life of most printers is 5-6 years.
The costs: Expect to pay a monthly fee. Costs are determined by
your choice in company and plan.
But by eliminating the risk of unplanned downtime, and by using a
company who supplies highly qualified operators, you’ll save the
expense of requiring additional staff to handle the assurance of OEE.
For instance, an entry-level product like CARE gives you predictive
analysis with scheduled inspection calls from a manufacturer-
trained professional who has the repair parts before you need them.
Equipment is only changed at the end of life, and all conditions are
assessed to predict damage before it occurs.
The next service level, CARE, is even more preventative. Offering the
same level of scheduled checks frequency, and data analysis (giving
each technician more information to work with), you can better
manage your equipment assets. Savings on discounted rates for
parts and maintenance are also advantageous.
The conclusion: In light of all of these factors, the Break Fix
approach seems akin to letting the oil run out on your car: it’s far
more expensive to blow a gasket than it is to get an oil change
regularly. With so many variables, expense piles up quickly, even for
smaller Australian manufacturers who are looking to keep expenses
low and grow relationships with retailers.
Unless you’re on an equipment lease program (saving short-term
capital) where you refresh your printers and equipment very four
years with the latest technology, the Reactive Maintenance approach
gives Australian Manufacturers additional ‘bad news’ such as the
hidden costs of letting your equipment go into decline.
To find out more about our preventive maintenance programs,
contact us today. See here also for why “an ounce of prevention
is worth a pound of cure”. You may also be interested why it’s
something contract packers should be aware of, while this blog
sets the difference between preventive maintenance vs breakdown
repair (it may be a surprise to know that the true cost of a machine
breakdown has been estimated as between 4 to 15 times the
maintenance costs — don’t get caught out: choose a local provider,
with 24-hour support). You may also be interested to see how
inefficient coding and labelling equipment can waste time, money
and resources, so check out 10 ways to optimise your current
operations.

The good news is Australian manufacturers don’t need to look far for the answer.
Consider this fact:
The true cost of a machine breakdown has been estimated is
between four to 15 times the maintenance costs per event.
So, if you want to be more cost-effective in the coming year, you
need to invest in preventative maintenance.
Failures and downtime happen in every manufacturing environment.
That’s the reality when you’re dealing with equipment that’s running
for hours every single day.
But if you are waiting until your equipment breaks down before doing
repairs, you are adding unnecessary costs and inefficiencies to your
business.
Not only do you have to the price of an emergency repair call-out,
you have to pay for any unplanned loss of productivity and wasted
resources too.
Unplanned downtime can lead to delays, which in turn results in
unhappy customers or even the loss of customers and a direct hit to
your bottom line.
According to Industry Week, “Unplanned downtime costs industrial
manufacturers an estimated $50 billion annually.” And equipment
failure is the cause of 42% of this unplanned downtime.
But it’s not just the downtime that hurts your business. If your
equipment starts to deteriorate without detection, your business
could be distributing products of lower quality without realising it.
We’re talking about inspection equipment that lets contaminants slip
through undetected, checkweighers that let containers pass through
with too much or too little inside, labels with unscannable barcodes
and illegible product codes, and more.
Before long, this will cost your brand in lost trust and customers.
How Preventative Maintenance
Saves Money for
Australian Manufacturerscode check capture care

What is preventative
maintenance?
Preventative maintenance, also known as planned maintenance, is a
proactive maintenance strategy designed to ensure your equipment
is operating at peak efficiency at all times.
Think of it like giving your car a service – most people book their
vehicle in for a service every 10,000 kilometres or so, rather than
waiting for it to breakdown.
Depending on the equipment, preventative maintenance might
include:
• Quick daily inspections
• Cleaning equipment
• Lubricating equipment
• Minor adjustments
Because you are monitoring the equipment, you can plan for
maintenance to be carried out during less costly times
Benefits of preventative
maintenance
1. Reduced waste
According to a McKinsey report, you can benefit from 10-20%
reduced waste. How? Because if your equipment is running at a
sub-optimal level, it will produce more waste. We’re not just talking
about raw materials, but also energy, labour costs and machine time.
Preventative maintenance processes can uncover and solve issues
that can result in waste.
2. Increased equipment life and lower TCO
This is the big one. Routine maintenance keeps equipment running
safely for as long as possible and lets you ultimately benefit from a
lower TCO, which improves your bottom line in the long run.
3. Uncover improvement opportunities
With automated data collection from equipment, and insights into
how the equipment is performing, Australian manufacturers can
uncover new opportunities for on process optimisation.
4. Detect and solve minor problems
Because staff are continually monitoring and maintaining equipment,
they can detect and solve minor problems before they become
bigger, more expensive problems.
5. Improved quality and precision
For coding, labelling and inspection equipment, preventative
maintenance is especially important for quality control. It ensures
labels are always printed to the highest quality and coding and
weighing is always precise. This prevents you from supplying
products that aren’t up to quality standards, and may be rejected by
customers.
6. Reduced spare parts and service charges
Without the need to for emergency repair call outs, you can
substantially cut spare parts and service charges. Unexpected
failures can mean having to pay technicians overtime and having to
pay extra for overnight delivery of parts.
7. Ongoing training for your staff
By delegating maintenance and care tasks to your team, you are
ensuring they are better training on the machines, which will ensure
they can better identify any potential problems.
8. Optimise employee productivity
Planned maintenance means you can better manage your resources,
staff and production schedules for optimal productivity. Think about
breakdowns from an employee’s perspective: downtime can impact
output and employee morale. They are stressful and disruptive.
Predictive maintenance means employees can be more productive.
Next steps
Preventive maintenance offers lots of important benefits, but the
most important is that it can improve your bottom line. Make
preventative maintenance part of your plan for the new financial
year. Talk to Matthews about our preventative maintenance service
plans. We have designed a range of scheduled service plans to
match our customers’ needs.

You know what they say: “If it ain’t broke, don’t fix it”. For decades, many
manufacturers have relied on a “fail and fix” approach for equipment, waiting until
the very moment it breaks down before fixing the problem. However, there’s a
growing school of thought that an alternative “predict and prevent” approach is the
best — and perhaps only? — way to run a production line.
So which should you choose?
Here we look at the pros and cons of each approach:
What you need to know about preventive
maintenance vs breakdown repair
By guest author, Mario Soccio*code check capture care

What is preventative
maintenance?
Preventative maintenance, or planned maintenance, is the process
of making sure that all equipment is operating at peak efficiency
at all times. Depending on the equipment, it may comprise quick
daily inspections, cleaning, lubricating and minor adjustments.
In the short term, this means minor problems can be detected
and solved before they become a major problem. And in the long
term, preventative maintenance helps you get the most from your
equipment for longer.
Think about your car. Most people don’t wait until it breaks down
before getting it serviced. Instead, you book it in for a service
every 10,000 kilometres or so. The same approach should apply to
labelling, coding and packaging equipment in your plant. And yet,
some manufacturers wait until their equipment fails before doing
anything about it.
What is breakdown repair?
Breakdown repair, or “fail and fix”, simply means that you wait for
equipment to fail before fixing it. This approach goes back decades,
founded on the belief that maintenance is unnecessary and costly. In
the past, maintenance has simply not been recognised as a task that
contributes to the bottom line. Instead, workers are focused on those
activities that are seen to directly impact productivity.
The cost factor
Let’s face it; everything comes down to the bottom line. So the
biggest question manufacturers want answered is what is the cost
of preventative maintenance versus breakdown repair?
On the surface, you might think that breakdown repair has the edge.
After all, you only need to budget for the one-time expense of repair
and parts, right? Wrong. The cost of breakdown repair extends far
beyond the repair labour and materials. Because a breakdown is
never planned, it causes production to stop for an undetermined
period. For every minute that production stops, the company is losing
money. It may miss deadlines, which impacts the rest of the supply
chain and can increase the risk of losing customers. It’s no surprise
then that the true cost of a machine breakdown has been estimated
as between four to 15 times the maintenance costs per event.
It’s not only the downtime that costs the business; if equipment
starts to wear without detection, a plant may be producing items
with unacceptable quality without realising it. We’re talking
about labels with unscannable barcodes and illegible product
codes, inspection equipment that lets contaminants slip through
undetected, checkweighers that let containers pass through with
too much or too little inside, and so on. Before long, this will erode
customer and consumer trust in your products and brand.
By maintaining your equipment on a regular basis, you are also
ensuring you get the most out of it. Because it’s working more
efficiently, you ultimately benefit from a lower total cost of ownership
(TCO) and a stronger return on investment (ROI) in the long run. (This
article explains what TCO is, while this one explains how reducing
TCO fits into improving your bottom line.)
The time factor
One factor that deters some manufacturers from preventative
maintenance is the time involved in checking and inspecting
equipment. It’s that there’s some investment required in setting up
a preventative maintenance program (PMP). A good maintenance
program demands company-wide support from the top executive
right down to the machine operators. However, once established,
the process of checking equipment is minimal compared with
the time that could be lost if a piece of equipment breaks down
without warning (not to mention the hassle and stress of getting the
machine up and running again).
While you can take a self-maintenance approach, most
manufacturers choose to take advantage of a dedicated service by
their equipment providers. This is often available for a monthly fee,
depending on the provider, but comes with the invaluable benefit
of access to highly qualified service technicians. For example,
Matthews provides a preventative maintenance program whereby
skilled technicians conduct thorough routine service procedures
and inspect your coding, labelling and inspection equipment. Where
required, the technicians replace consumable parts, clean equipment
and advise
The verdict
The time for breakdown repair is long gone, and any company that
wants to continue growing and generating profits needs to invest in
preventative maintenance.
The good news is that there are smart technologies designed to
make preventative maintenance easier and more cost-effective than
ever. The current labelling and coding machines, for example, are
fitted with sensors that can check the output quality and warn of
potential issues long before the machinery breaks down and brings
production to a grinding halt.
Data-capture solutions can also be integrated into the production
line to monitor performance and provide visibility and access to data
across the line. Matthews’ iDSnet software is one such example of
a data-capture solution designed to see, interpret and communicate
exactly what’s happening on the factory floor. (Download the
Intelligent Software Solutions brochure for more detail.) Together,
these technologies help manufacturers not only prevent equipment
breakdowns but drive overall equipment effectiveness (OEE)
and improve efficiency. (See here for a blog on OEE and here for
technologies, solutions, industries, videos and a free whitepaper to
download on OEE and harnessing the power of metrics.)
Get more tips here on building a successful planned maintenance
program. You can also read about why scheduled maintenance
is the “ounce of prevention that’s worth a pound of cure”, how
planned maintenance is one of the 12 most important metrics to
measure in manufacturing and how important TPM (total productive
maintenance) is to Australian manufacturers. And then, why
choosing a local provider, with 24-hour support, puts you in front.
You may also find this whitepaper interesting; it looks at the
primary objective of preventative maintenance in maximising your
equipment’s performance by keeping it running safely for as long as
possible, without deteriorating or unplanned, costly failures.
Matthews has a vast library of whitepapers, industry presentations,
case studies, detailed infographics, production-line videos, FAQ’s,
news, brochures, datasheets and thought leader articles. And they’re
free to download!

code check capture care 24x7
1300 263 464 www.matthews.com.au
About Matthews Australasia
Matthews Australasia, a family business, is Australia’s leading provider of intelligent product
identification and product-traceability solutions, offering inkjet, thermal transfer, laser, label
applicators, label print and apply systems, RFID, barcode-scanning solutions and machine
vision inspection. All these solutions can be integrated with Australia’s first identification
networking and reporting software, iDSnet, winner of 2011 APPMA Design Award.
Solutions-focused, Matthews helps customers with business efficiencies and cost savings by providing production
intelligence and increased automation.
Matthews’ unmatched solution capability is backed by 24x7 technical support and customer service to support all
installations across the country to give you peace of mind. Streamlining ensures less downtime for customers and Matthews’
first-time x rate is 97%.
No matter what your coding, labelling or data capture application, Matthews is the only company in Australia that can provide
you with a complete range of end-to- end intelligent identification solutions.
To find out more about how Matthews can be of service to you, call 1300 263 464, visit www.matthews.com.au or email
info@matthews.com.au.

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