Prod in Automation

8/9/2019 Prod in Automation

1/13


2/13

robotics industry, and sales6orders for the first half of 52/1 have continued to push the bar

higher. he 7obotic Industries &ssociation estimates that some 512,222 robots are now in use

in U.S. factories, placing the United States second only to 8apan in robot use.

he potential for continued growth is significant as advanced manufacturing processescontinue to gain a foothold. Some industry sources estimate that only about /2 percent of

U.S. companies that could benefit from robots have so far installed them. In particular, the

122,222#plus small to medium#si9ed U.S. manufacturing companies represent significant

growth opportunities as more of those firms embrace automation, notes (oyle. :actors that

will continue to fuel that growth include reduced costs for robotics systems, as well as an

e3plosion of new technologies in the robotics field that have made user interfaces simpler,

improved gripper technology, and created better vision#guided systems that have opened up

new manufacturing opportunities for the use of robots.


3/13

Making the future

How robots and people team up to manufacture things in new

ways

&pr 5/st 52/5 ; from the print edition

"&< I! += />?2s, when &merica@s carmakers feared they might be overwhelmed by

8apanese competitors, many in (etroit had a vision of beating their rivals with “lights#out”

manufacturing. he idea was that factories would become so highly automated that the lights

could be turned off and the robots left to build cars on their own. It never happened. 8apan@s

advantage, it turned out, lay not in automation but in lean#production techni4ues, which are

mostly people#based.

http://www.economist.com/printedition/2012-04-21http://www.economist.com/printedition/2012-04-21


4/13

$any of the new production methods in this ne3t revolution will re4uire fewer people

working on the factory floor. hanks to smarter and more de3terous robots, some lights#out

manufacturing is now possible. :&!U, a big 8apanese producer of industrial robots, has

automated some of its production lines to the point where they can run unsupervised for

several weeks. $any other factories use processes such as laser cutting and injectionmoulding that operate without any human intervention. &nd additive manufacturing machines

can be left alone to print day and night.

Aet manufacturing will still need people, if not so many in the factory itself. &ll these

automated machines re4uire someone to service them and tell them what to do. Some

machine operators will become machine minders, which often calls for a broader range of

skills. &nd certain tasks, such as assembling components, remain too fiddly for robots to do

well, which is why assembly is often subcontracted to low#wage countries.

Industrial robots are getting better at assembly, but they are e3pensive and need human

e3perts to set them up Bwho can cost more than the robotC. hey have a long way to go before

they can replace people in many areas of manufacturing. Investing in robots can be

worthwhile for mass manufacturers like carmakers, who remain the biggest users of such

machines, but even in highly automated car factories people still do most of the final

assembly. &nd for small and medium#si9ed businesses robots are generally too costly and too

infle3ible.

"ut the ne3t generation of robots will be different. !ot only will they be cheaper and easier to

set up, they will work with people rather than replacing them. hey will fetch and carry parts,

hold things, pick up tools, sort items, clean up and make themselves useful in myriad other

ways.

Darious efforts are under way to produce such robots, especially for smaller companies.

)ermany@s :raunhofer Institute, for instance, is involved in a =uropean initiative to develop

robots that are safe enough to operate alongside workers Bat present, most industrial robots

still have to be caged in case they accidentally hit someoneC and capable of understanding

simple instructions, including voice commands.

he present generation of factory robots is akin to early mainframe computers in offices,

reckons 7odney "rooks, a co#founder of i7obot, an &merican firm whose products include

the 7oomba, a robotic vacuum#cleaner, as well as military robots. hose big computers were

run by e3perts, a long way away from most users, until personal computers arrived. “"ut the

E didn@t get rid of office workers, it changed the tasks they did,” says $r "rooks. 'ften that

meant doing more sophisticated work. In 522? he founded +eartland 7obotics to produce a

range of machines that would serve as the e4uivalent of the E in robotics.

$r "rooks@s lips are sealed about what these machines will be like, although his views aboutthe future of robotics provides a clue. &s oyota discovered with lean manufacturing,


5/13

production#line workers, given the chance, can come up with plenty of good ideas to improve

productivity. If people on the factory floor or in workshops are provided with easy#to#use

robots they can become more productive, says $r "rooks. "ring together these new robots

with innovative manufacturing technologies, and you could get a manufacturing renaissance.

$illions of small and medium#si9ed firms will benefit from new materials, cheaper robots,

smarter software, an abundance of online services and 1( printers

hat would make things easier for start#ups, but scaling up is notoriously difficult because the

capital costs of e4uipping a factory are often too high for investors to stomach, or the

payback period is too long. In some businesses advanced production technologies could bring

down those costs, reckons $artin Schmidt, an electrical#engineering e3pert at $I. $r

Schmidt has started a number of companies that make tiny devices such as miniature sensors.

+e thinks that the production e4uipment for such devices might be shrunk too, even totabletop si9e, cutting capital costs. In industries where that happens, says $r Schmidt, “I

think we will see some disruption.”

$ass#produced goods will continue to be made in factories using traditional subtractive

methods for a long time yet, although with increasing automation and fle3ibility, as practised

by the mass#market carmakers. here will also be some super#high#tech factories, like those

of )= and 7olls#7oyce, that make smaller 4uantities of highly specialised products such as

jet engines. here will be millions of small and medium#si9ed firms that will benefit from

new materials, cheaper robots, smarter software, an abundance of online services and 1(

printers that can economically produce things in small numbers. &nd there will be countless

entrepreneurs in little workshops, homes and, no doubt, garages who will be able to do things

they could never have done before.

Getting there

$anufacturing revolutions never happen overnight, but this one is already well under way.

here is enough transformative research going on in the biological sciences and in

nanotechnology to spawn entirely new industries, like making batteries from viruses. &nd if

the use of carbon#fibre composites were to spread from sports cars to more workaday models,

the huge steel#stamping presses and robot welding lines would vanish from car factories.

&dditive manufacturing, like anything else digital, is already becoming both cheaper and

more effective. he big breakthrough would be in workflow. &t present 1( printers make

things one at a time or in small batches. "ut if they could work in a continuous processFlike

the pill#making machine in the !ovartis#$I laboratoryFthey could be used on a moving

production line. he aim would be to build things faster and more fle3ibly rather than to

achieve economies of scale. Such a line could be used to build products that are too big to fit

into e3isting 1( printers and, because the machine is digitally controlled, a different item


6/13

could be built on each platform, making mass customisation possible. hat would allow the

technology to take off.

an it be doneG "ack to the =uro$old e3hibition, where !', an independent research

group based in the !etherlands, showed a novel machine with /22 platforms travellingaround a carousel in a continuous loop. & variety of 1(#printing heads would deposit plastics,

metals or ceramics onto each platform as they pass to make complete products, layer by layer.

Scale up the idea, straighten out the carousel and you have a production line with multiple

printing heads.

he “+ammering $an” outside the :rankfurt $esse is still bashing away at his piece of

metal. "ut in a decade or two visitors to future industrial fairs may wonder what he is doing.

:rom the print editionH Special report

The Dangers of Process Automation

%hen attempting to improve process performance, automation is a tempting solution. %hile

automation can be very effective, other process problems should be addressed first in order

for an investment in automated systems to pay off.

$ost of us need our processes, particularly our production processes to happen faster and at

less cost. & common go#to solution is to invest in automating manual processes.

&utomation offers two#fold benefits. &utomated processes are generally faster, and once

tuned in, they also boast better, more consistent, 4uality because they eliminate human error.

his is generally true.

&utomated processes are much like computers, however. hey do e3actly what we tell them

to do or what they are programmed to do. hey don*t always do what is right. If we don*t

error#proof the process before automating it, or at least while automating it, then automation,

instead of eliminating waste, tends to produce more waste faster. It is my e3perience that

automation succeeds best if it is the last improvement to a process. It disappoints when it is

the first.

& few years ago I helped to institute a standard, enterprise#wide, automation of =ngineering

hange B=C and document control processes as part of the institution of an =nterprise

http://www.economist.com/printedition/2012-04-21http://www.economist.com/printedition/2012-04-21


7/13

7esource Elanning B=7EC and $anufacturing 7esource Elanning B$7EC system. &t that time

there were several design and manufacturing centres, each using its own = system and rules.

In one centre in particular, two people worked full#time to manage the = process. It had

many facets to it that re4uired some intelligence. 'ne in particular was that a large number of

people needed to be notified of engineering changes and each had the privilege of approving

each one to indicate that the change was reviewed.

Aou might imagine the waste that went with such behaviour. he = process people had to

manually determine from the rule set who needed to approve each = and e#mail it out. hen

the = would wait in e#mail bo3es for someone, sometimes someone who had much bigger

concerns than an =, to get around to reviewing the = and responding.

o keep =s from being help up eternally, if no response was received within a week, the

process people would begin to make phone calls and leave voice messages. If after threeweeks there was no response, it would automatically be approved and would move on to the

rest of the process.

Aou can see, from just that one e3planation of a minor portion of the process, why people

were dedicated to managing the process. !ow let*s imagine automating that process.

If the e3ample were automated as is, how fast would a large number of people get their e#

mail bo3es filled up with = re4uestsG 'bviously, it would occur as fast as engineers could

produce them. !ow consider that the process people did a 4uality screening function as well

and kicked back any incorrectly applied or incomplete = re4uests back to the engineers before e3ecuting the process.

&n automated process might not include that function. So, not only is all of the over#

processing, overproduction, and waiting waste taking place, it is also producing all of the

defective =s that are input into the system. !ow, to correct the errors, all of that waste has

to also be repeated. 'bviously, more waste for everyone to deal with, more often, is not what

we wanted from an automated process.

Instead, what we did is reduce the = process to its most fundamental, essential elements. %e

had to redefine some beliefs and alter some authority in order to reduce review and approval

to a single person per = instead of many. %e error#proofed the re4uest system and

eliminated the options and decisions as much as possible. Aes, we gave up a great deal of

fle3ibility, but we also unloaded an enormous amount of waste.

'nce the process was simplified and error#proofed as much as possible, we instituted the

automated system according to the simplified solution. ife was much better before everyone,

e3cept perhaps the dedicated = process people who were routed to alternative

responsibilities. In the end, after adjusting, I think life was even better for them. heir new

responsibilities were more meaningful Bno one likes being a monitor of wasted time andenergyC.


8/13

he same phenomenon occurs with automated production processes. %e often justify

investing in automated e4uipment by calculating improvements in production time and

reduction of errors and defects. +owever, if a bad input is inserted into an automated system,

a bad output occurs faster, consuming materials and resources faster.

"ad inputs to automated processes can come from a wide variety of sources.

Eoor materials.

Eoor programming.

Incorrect assumptions or settings.

Eoor process design.

ack of control.

oo much adjustment or over#control.

Instability in the process or environment.

Eoor timing. oo many initiated.

oo few initiated.

Incorrect order initiated.

&bove are a few common sources. Specific processes will have specific errors that can occur.

If the sources for error are not addressed prior to instituting automation, the errors will still

occur. hey might occur more often because there is no longer an intelligent person in the

process to recogni9e when something is in error and call for a correction before the output is

complete.

If the first opportunity to recogni9e and correct an error is after the output is complete or

when the system fails because of the error, then the automated system will drive more

e3pense and defects and down#time instead of save it.

"efore automating any process, break that process apart and work diligently to remove the

waste and errors from it. &s I wrote above, an automated process does what it is told. Eoor

inputs result in poor outputs. $ake sure that the process you automate is a solid, error#proof,

consistent, and reliable process.

he misperception about automation is that automated processes are by nature error#proof

and faster. It is not so. 'nly a good, error#proof process that is automated in a reliable manner

will be faster with better 4uality.

ake this message away from this post. &utomate a process only after you have applied the

other process improvement tools and methods to reduce opportunities for error, eliminate

waste, and improve consistency. It may be that such is done while developing or

programming the automated system, but it must be done first. 'therwise, the waste and error

occurring within or as an output will undermine the business plan that justified the

investment.


9/13

Revolutionising Sensor Based Automation in

Manufacturingby R Harrison, F Jammes, H Smit and T Kirkham

ncreased access to device!level automation components is closing the final gap in the

enterprise computing model.

he implementation of %eb service#enabled sensors and actuators on production lines will

permanently change the way in which future automation systems are designed and

implemented. urrent interfaces to automation components are largely vendor#specific,

restricting the reconfiguration of lines and the management of line data across enterprises.

'utside the automation domain, enterprise system development has seen real#time data

linkage take great steps in the office, warehouse and supply chain. 7esearch into the use of

%eb#service#enabled sensors and actuators has the potential to present an open standards#

based method to integrate production lines into this enterprise computing model, an

innovation that will revolutioni9e automation in future manufacturing plants and remove

control from vendors back to users.

mplementation

he S'7&(=S and S'(& BService#'riented (evice and (elivery &rchitectureC projects

have conducted research and trials into automation based on service#oriented architecture

BS'&C, and in the past year have delivered initial prototypes. &t the recent I=& e3hibition in

7otterdam, a test rig developed with :ord was used to demonstrate S'based sensor and

actuator data being used to manage monitoring and control applications. he data was fed to

project partners in the =nterprise computing field BS&EC and industrial automation sector

B&7 Informati4ueC. he demonstrator illustrated how the production data could be

combined with other enterprise data to improve the accuracy of decisions relating to production routing and supply chain management.


10/13

:igure /H Dision of service#enabled automation.

(uring the demonstration, data from the sensors and actuators on the production line was

transmitted by e4uipment created by Schneider =lectric. his e4uipment consisted of %eb#

service#enabled :ield erminal "locks B:"sC, which support the (evice Erofile for %eb

Services B(E%SC toolkit. he (E%S toolkit is designed for embedded systems and has asmall memory footprint, but also contains a selection of %eb service standards to suit the

demands of an automation environment. "oth projects are working on these demands, which

are focused on e3ecution timing and reliable6efficient message delivery. he :" is a piece

of hardware that contains an &7$ > chip developed to support the (E%S toolkit.

he support of (E%S on the :" allows %eb service interfaces to be developed to the

device#level I6' within the line. :or e3ample, calls to directly command an actuator or

monitor specific sensors on lines can be made via %eb services located on a variety of

applications, as opposed to specific vendor control devices. he control of devices by %eb

services has been achieved using central %eb service orchestration and also on a smaller#

scale peer#to#peer choreography.

:igure 5H I=& e3hibition architecture and rig picture showing :" location.

Future

(evice#level automation components that produce data in standard and open forms will be

faster to reconfigure, reducing costs by improving resource usage and reducing downtime.

he greater accuracy and real#time access to product#level data will further enhance

enterprises by allowing them to make more accurate decisions regarding production andsupply chain matters. he application of the results from these research projects in real

manufacturing environments will be the subject of future work that should confirm these

findings. he adoption of the approach will also be dependent on further research in the areas

of safety, security and real#time e3ecution of devices.

(irect S'& linkage to sensors and actuators moves a traditionally vendor#specific computing

area into a new open domain, ready to link with e3isting innovations in enterprise computing.

:or the manufacturer this will improve performance and reduce costs. +owever, this is

dependent on the continued development of devices such as the :", pioneered in the

S'7&(=S and S'(& projects to support this new vision.


11/13

How IoT big data will transform manufacturing automation

"y $ary Shacklett September 5?, 52/J, //H/> E$ ES

:ind out how big data and Internet of hings contribute to smart manufacturing automation, which

may benefit everyone in the supply chain.

Imagine a world where smart systems, Internet of hings BIoC sensors, and robotics combine

to automate large areas of manufacturing, linking wired and wireless networks throughout the

world in the making of products, and relying on both structured and unstructured big data to

get the job done. $c


12/13

7eali9ing the potential of a total manufacturing transformation with use of Io big

data, )ermany initiated its Industry J.2 government initiative to spur its industrial sector.

(ependent upon real#time big data for driving and making decisions in the factory, Industry

J.2 represents, according to pundits, the Lfourth industrial revolutionL ## following the steam

engine, the conveyer belt, and the first phase of I automation. In this world, multiple

factories, logistics providers, etc., will interconnect with each other in a system of people#

originated and Io big data automation ## all controlled by a central system Lback planeL that

is capable of synchroni9ing and orchestrating all events throughout the supply chain and

giving everyone involved full visibility of what is going on.

o e3ecute the smart manufacturing vision, enterprise systems must be modified so they can

interface with and monitor Io sensor#based technology, along with a host of disparate

manufacturing, logistics, procurement, order, and other systems that must be integrated into a

single back plane system. :rom an I perspective, the task can be daunting. :rom a vendor

management perspective, there can also be looming challenges, as some vendors will be more

prepared than others to participate in the effort.

=4ually important will be the need to bring together the big data team with the standard data

team, because for Industry J.2#style manufacturing to work, both big and standard data must

work together and be tightly integrated. his means getting both data teams engaged in a joint

project so information flows can be architected that draw upon both standard and big data to

drive the automation needed to run the factories. If factories are spread across different

suppliers and geographies, there will also be a need to import that big and standard data

architecture to others who are part of the manufacturing supply chain.

he good news is that industry standards are emerging for big and standard data interfacesthat will facilitate smart manufacturing information flows.

In industries like food and beverage, sensors that generate machine#driven information and

automatic alerts already are widely used to measure the temperature and the humidity of

containers that food products are shipped in, and also to track shipments from their points of

origin to their final shipping destinations.

Lhe presence of standards and regulatory compliance re4uirements is one of the major

drivers for the implementation of sensor systems,L said D. Sankarnarayanan, a :rost K

Sullivan senior industry analyst in measurement and instrumentation. L)overnments acrossthe globe have strict laws that mandate the use of sensors and other electronic devices that

sense the risk involved in food contamination.L

&utomatically subscribe to ech7epublic@s "ig (ata &nalytics newsletter.

Subscribe

:or big data, the move to smart manufacturing systems will be transformational. "ig data will

be called upon to Lrun things,L and not just to deliver analytics.

Lasks that are currently still performed by a central master computer will be taken over bycomponents,L said Eeter Eost, head of corporate research K program strategy at :esto. Lhese

http://www.bmbf.de/en/19955.phphttp://www.foodproductiondaily.com/Processing/Food-industry-appetite-for-sensors-increasinghttp://www.automationworld.com/chemical/future-manufacturing-industry-40http://www.bmbf.de/en/19955.phphttp://www.foodproductiondaily.com/Processing/Food-industry-appetite-for-sensors-increasinghttp://www.automationworld.com/chemical/future-manufacturing-industry-40


13/13

will network with one another in an intelligent way, carry out their own configuration with

minimal effort and independently meet the varying re4uirements of production orders.L

&s big data and Io remakes factories into optimi9ed and highly automated plants, goods will

achieve greater speeds to market, with stepped up profits for companies since more goods can

be routed to market faster. Erogressive companies are already investing in Io#driven

systems, which they believe will enable faster responses to changes in consumer demand and

product innovation. his potentially opens up greater market opportunities for companies and

more options for consumers ## which benefits everyone in the value chain.

Prod in Automation

Documents

Transcript of Prod in Automation