HOW TO BUILD SMART FAC­TO­RIES

Stitch World - - NEWS - Lately, some of the peo­ple in this busi­ness have started trans­form­ing dig­i­tally to gain crit­i­cal in­for­ma­tion and gen­er­ate in­sights. The im­por­tance of data lies not just in un­der­stand­ing the pro­cesses and tak­ing dis­cus­sions ahead based on that. It has reac

In re­cent years, ‘smart things’ have swamped our lives whether in the form of smart homes, smart watches, smart cars or smart­phones. All these de­vices are driven by tech­nol­ogy and up­graded within the soft­ware. But con­sid­er­ing the ap­parel in­dus­try, the dawn of smart fac­to­ries is driven by mar­ket pull. Ev­ery year, the buy­ers visit sup­pli­ers and ask for cost slash, thus plac­ing or­der in small quan­ti­ties, and this has ad­versely im­pacted the busi­nesses of many Asian coun­tries as they face a huge crunch in prof­its. Build­ing ‘Smart Fac­to­ries’ can be a so­lu­tion. Team StitchWorld, with the help of two in­dus­try ex­perts, one from within the ap­parel in­dus­try and the other hav­ing di­verse in­dus­try ex­pe­ri­ence, discuss about how to go about build­ing smart fac­to­ries. Smart fac­tory and the po­si­tion of the ap­parel in­dus­try…

Smart fac­tory in­cludes a com­bi­na­tion of pro­duc­tion, in­for­ma­tion and com­mu­ni­ca­tion tech­nolo­gies, with the po­ten­tial for in­te­gra­tion of these tech­nolo­gies across the en­tire man­u­fac­tur­ing sup­ply chain. The core lies in data col­lec­tion and mak­ing real time dis­cus­sions based on that. IT and au­to­mo­tive in­dus­tries are fron­trun­ners when it comes to build­ing smart fac­to­ries. How­ever, as far as the ap­parel in­dus­try is con­cerned, the trans­for­ma­tion of tra­di­tional fac­to­ries into smart fac­to­ries is not be­ing seen on a larger scale. To­day when ev­ery­thing is be­ing digi­tised, the ap­parel man­u­fac­tur­ers need to pur­sue in­no­va­tion much be­fore their com­peti­tors do. There are plenty of tech­nolo­gies avail­able in the mar­ket for that which help the busi­nesses in achiev­ing suc­cess and main­tain­ing pace with the rapidly trans­form­ing world. But us­ing the tech­nol­ogy in the right way and in the right place will help the busi­nesses achieve ul­ti­mate suc­cess.

Why to bring smart tech­nol­ogy in…

In or­der to bring down the cost of man­u­fac­tur­ing, many buy­ers have started procur­ing from cheap African man­u­fac­tur­ing des­ti­na­tions such as Ethiopia, Mada­gas­car and Mau­ri­tius as well as emerg­ing Asian hubs in­clud­ing Myan­mar and Cam­bo­dia. “This shift to­wards Africa and low-wage coun­tries in Asia is pri­mar­ily due to the avail­abil­ity of re­sources, but what next af­ter ex­plor­ing these coun­tries…,” pointed out Imal Ka­lu­to­tage, Chief Ex­ec­u­tive Of­fi­cer, n-Cinga In­no­va­tions, Sri Lanka. It’s be­come a widely known fact that, of late, the main pil­lars for main­tain­ing a good re­la­tion­ship with buy­ers and most im­por­tantly sur­viv­ing in the ap­parel busi­ness are on-time delivery of the prod­ucts and main­tain­ing the good qual­ity of the same. But from quite some time, these two as­pects, how­ever, have not been able to reap ex­tra prof­its for the ap­parel man­u­fac­tur­ers, thus mak­ing it chal­leng­ing for them to sur­vive in this fierce com­pe­ti­tion. Af­ter shift­ing the base to other un­der­de­vel­op­ing na­tions, there will be no scope to break­down the man­u­fac­tur­ing cost and the only thing left will be to bring in tech­nolo­gies and digi­ti­sa­tion for con­tin­u­ous im­prove­ment in terms of pro­duc­tiv­ity, ef­fi­cien­cies and qual­ity.

Ac­cord­ing to Jagdish Ra­maswami, Chief Dig­i­tal Of­fi­cer and Head of Busi­ness Ex­cel­lence, Hin­dalco In­dus­tries Ltd., Aditya Birla Group, go­ing dig­i­tal to set up a smart fac­tory of­fers nu­mer­ous ways to suc­cess­fully achieve greater ef­fi­ciency and higher pro­duc­tiv­ity. “Set­ting up a smart fac­tory of­fers the abil­ity to ad­just and learn from data in real time and can make the smart fac­tory more re­spon­sive, proac­tive and pre­dic­tive and en­ables the or­gan­i­sa­tion to avoid op­er­a­tional down­time and other pro­duc­tiv­ity chal­lenges,” said Jagdish ad­ding that, “It’s only the right type of data be­ing used at the right place and the right peo­ple be­hind it that help in mak­ing the sig­nif­i­cant changes.”

How­ever, most of the or­gan­i­sa­tions think that tech­nol­ogy is ex­em­plary and can fix ev­ery­thing but the fact is it can­not. Imal quoted with an ex­am­ple, “Buy­ing a new car is not enough as the buyer should know how to run it and what all is re­quired to main­tain it with time.” Sim­i­larly to make a tech­nol­ogy work, the com­pany should be aware about the plat­form it is run­ning on and what all the

pro­cesses that are needed to run the tech­nol­ogy ef­fi­ciently. In or­der to achieve this, the com­pany should prop­erly train the em­ploy­ees on tech­nol­ogy. “Many

ERP im­ple­men­ta­tions fail mis­er­ably as the com­pa­nies are not aware about the pro­cesses such as tech­nol­ogy upgra­da­tions and the main­te­nance re­quired so as to make them run ef­fi­ciently,” shared Imal.

What it takes to build a fac­tory that is smart…

The term ‘Smart fac­tory’ de­scribes an en­vi­ron­ment where ma­chin­ery and equip­ment are able to im­prove pro­cesses through au­to­ma­tion and self­op­ti­mi­sa­tion. It rep­re­sents a leap for­ward from more tra­di­tional mech­a­ni­sa­tion to a fully con­nected and flex­i­ble sys­tem, one that can use a con­stant stream of data from con­nected oper­a­tions and pro­duc­tion sys­tems in or­der to learn and adapt to new de­mands.

Smart fac­to­ries are be­ing im­ple­mented in other in­dus­tries such as au­to­mo­bile and steel in­dus­try. They are highly au­to­mated, mak­ing it much eas­ier to cap­ture data whereas there are cer­tain chal­lenges that pose hin­drance while adopt­ing this con­cept in the ap­parel in­dus­try. As of now, the in­dus­try is very hu­man­cen­tric, less au­to­mated and is in­creas­ingly be­com­ing chal­leng­ing with small or­der quan­ti­ties. Con­nect­ing the sewing ma­chines is one way to cap­ture the shopfloor data, but the big­ger prob­lem lies in han­dling the large amount of data gen­er­ated. The ques­tion is how to cap­ture data from hu­mans and the prod­ucts in the gar­ment fac­tory which are not that smart.

There are var­i­ous tools of In­dus­try 4.0 that have made it pos­si­ble to cap­ture the data in an ef­fec­tive way in man­ual en­vi­ron­ment us­ing de­vices and hard­ware such as RFID/ NFC, ma­chine vi­sion, QR/Bar codes, touch and sen­sors. By im­ple­ment­ing these de­vices/ tools in the fac­to­ries, most of the projects are be­com­ing cost-prof­itable.

On a mis­sion to em­power the data-driven de­ci­sions to help build smart fac­to­ries, CEO of n-Cinga In­no­va­tion as­serted the need of dis­rup­tion in the ap­parel in­dus­try. In­for­ma­tion and com­mu­ni­ca­tion tech­nol­ogy is un­der­go­ing a rapid de­vel­op­ment and many dis­rup­tive tech­nolo­gies in­clud­ing cloud com­put­ing, In­ter­net of Things, big data and artificial in­tel­li­gence have emerged. These tech­nolo­gies are per­me­at­ing the man­u­fac­tur­ing in­dus­tries and en­able the fu­sion of phys­i­cal and vir­tual world through cy­ber-phys­i­cal sys­tems which marks the dawn of In­dus­try 4.0.

“For in­stance, the mo­ment we book Uber cab, Uber al­lows us to use live-track­ing so as to know the ex­act lo­ca­tion of the driver as well as shows the es­ti­mated time of ar­rival to reach the des­ti­na­tion. Con­sid­er­ing the ap­parel fac­tory, when a buyer wants to know the sta­tus of the or­der, the an­swers are ei­ther dated to yes­ter­day or an hour ago,” boasted Imal.

With live-track­ing fea­ture on the shopfloor just like Uber, mer­chan­dis­ers and buy­ers would be able to fetch in­for­ma­tion re­lated to their or­ders. Buy­ers would be able to know the ex­act num­ber of units pro­duced at a par­tic­u­lar time. It is very ben­e­fi­cial for the sup­pli­ers. With real time data track­ing, the work­ers in the fac­tory would be aware about their hourly tar­get based on the pro­duc­tion and would know the ex­act amount of in­cen­tives they have earned.

Imal men­tioned, “In or­der to dis­rupt the busi­ness model and make it ag­ile, you need to dis­rupt the cur­rent oper­at­ing model. And this can only hap­pen with the help of ag­ile dig­i­tal in­fra­struc­ture. The prime com­po­nents of this dig­i­tal in­fra­struc­ture are cloud, sen­sors, 3D print­ing, data an­a­lyt­ics and M2M robotics.”

The de­fects which can be de­tected at a very early stage rather than at end line sta­tion can help in bringing down the rate of re­jec­tion and re­works by eas­ily iden­ti­fy­ing the cause of the prob­lem, be it ma­chine or hu­man er­ror. For ex­am­ple, with the help of data track­ing, three de­fects per sec­ond would be known at a very early stage and re­work can be ini­ti­ated eas­ily. This will not only im­prove the pro­duc­tiv­ity and ef­fi­ciency but also help dur­ing the time of in­cen­tives.

How is n-Cinga as­sist­ing to bring in change...

n-fac­tory is a next gen­er­a­tion smart fac­tory so­lu­tion by n-Cinga that dig­i­tally cap­tures the events of a

Smart fac­to­ries are be­ing im­ple­mented in other in­dus­tries such as au­to­mo­bile and steel in­dus­try. They are highly au­to­mated, mak­ing it much eas­ier to cap­ture data whereas there are cer­tain chal­lenges that pose hin­drance while adopt­ing this con­cept in the ap­parel in­dus­try.

fac­tory in real time and makes the most te­dious repet­i­tive tasks sim­ple by us­ing the smart au­to­ma­tion tech­nolo­gies. This cut­ting edge so­lu­tion will elim­i­nate the use of large num­ber of sen­sors and re­place them with de­vices and cam­eras to cap­ture events from com­monly used ges­tures of pro­duc­tion work­ers on pro­duc­tion floors.

“We do not cap­ture data, but the events. A sin­gle event can con­sist of mul­ti­ple events,” clar­i­fied Imal.

Once the events are cap­tured, they are pro­cessed in real time in the cloud. The soft­ware so­lu­tion then ap­plies the ma­chine learn­ing tech­niques to the events cap­tured so as to de­tect the anom­alies. A de­tailed re­port con­tain­ing the in­sights and anal­y­sis can be eas­ily viewed on a smart­phone de­vice. “n-Fac­tory cre­ates a ‘dig­i­tal twin’ of the fac­tory as it pro­vides the real time vir­tual map of the fac­tory with op­er­a­tional in­sights on the go,” said Imal.

Each fac­tory is viewed as a com­bi­na­tion of sta­tions such as cut­ting, sewing, wash­ing, fin­ish­ing and pack­ag­ing and ship­ping. These sta­tions are de­clas­si­fied into sub-sta­tions, for in­stance in the cut­ting de­part­ment, the sub-sta­tions will in­clude de­part­ments like lay­ing, cut­ting, bundling and num­ber­ing. The events are cap­tured at the in­put of the sta­tion, in-be­tween the sta­tions and at the out­put of the sta­tions. Each and ev­ery event hap­pen­ing in the fac­tory is mea­sured as ei­ther count­ing or qual­ity or down­time. “With these three as­pects, we can eas­ily model the fac­tory and then de­rive the WIP and KPIs”, said Imal. Each event can then be stud­ied and an­a­lysed for a num­ber of as­pects such as the top five down­time rea­sons, root cause anal­y­sis, pre­dic­tive main­te­nance, num­ber of re­works/re­jects/ good gar­ments, WIP and or­der rec­on­cil­i­a­tion, etc. These events, when com­bined with the work­flow, are used to cre­ate a dig­i­tal print of the fac­tory in a bet­ter way or what the com­pany calls ‘dig­i­tal twin’. In a nut­shell, n-Fac­tory al­lows a real time vir­tual map of the fac­tory and the per­son can search any as­pect about any or­ders.

This ground-breaking tech­nol­ogy so­lu­tion has been im­ple­mented in Sri Lanka and Bangladesh. The use of the com­pany’s so­lu­tion has al­lowed pa­per­less op­er­a­tion and real time vis­i­bil­ity. Imal men­tioned that the turn­around time for a sam­ple was re­duced to three days from three weeks and the ef­fi­ciency in­crease was recorded at 10 per cent. More­over, the qual­ity de­fects per month also re­duced to half. The so­cial im­pacts are note­wor­thy since it mo­ti­vated the work­ers. Higher mo­ti­va­tion and in­creased col­lab­o­ra­tion among the work­ers led to the in­crease in pro­duc­tiv­ity.

“The af­ford­abil­ity of the so­lu­tion can be de­cided from the fact that ROI of this prod­uct is achiev­able in less than six months,” con­cluded Imal.

How is Hin­dalco In­dus­tries as­sist­ing to bring in change...

Dig­i­tal in­no­va­tion is to­day’s mantra to main­tain the pace of change or lose rel­e­vance in the mar­ket. The steel in­dus­try gi­ant Hin­dalco In­dus­tries has trans­formed its fac­to­ries into smart fac­to­ries. Jagdish Ra­maswami has dis­cussed how ap­parel in­dus­try can reap the ben­e­fits of smart fac­to­ries in or­der to com­pete with oth­ers in this ap­parel busi­ness.

It’s a fact that data an­a­lyt­ics can­not be done for the en­tire areas within an in­dus­try. The iden­ti­fi­ca­tion of the crit­i­cal areas in the pro­cesses and col­lec­tion of data is the right way in or­der to get higher out­puts. Any tech­nol­ogy should not just be im­ple­mented be­cause it’s new and has proved suc­cess­ful to oth­ers. A proper anal­y­sis de­ter­min­ing the crit­i­cal paths and the areas where the tech­nol­ogy is re­quired should be the first step to­wards im­ple­ment­ing the tech­nol­ogy. “De­spite be­long­ing to the steel in­dus­try, I can say there are so many areas in the steel in­dus­try which are more or less sim­i­lar to the ap­parel in­dus­try and where dig­i­tal trans­for­ma­tion can ac­tu­ally take place. Safety is one of the areas,” averred Jagdish.

Ac­cord­ing to him, the gar­ment in­dus­try should fol­low a prac­tice where each of the man­agers should have an app in their mo­bile phones and that should in real time tell them who in the fac­tory is mov­ing in un­safe zones. This alert will make them aware about the un­safe prac­tices be­ing fol­lowed by their sub­or­di­nates and they can take im­me­di­ate preventive ac­tions for the same. “In our in­dus­try, we are fol­low­ing this prac­tice,” claimed Jagdish.

Fur­ther­more, start­ing with the iden­ti­fi­ca­tion of areas that are crit­i­cal to the

It’s a fact that data an­a­lyt­ics can­not be done for the en­tire areas within an in­dus­try. The iden­ti­fi­ca­tion of the crit­i­cal areas in the pro­cesses and col­lec­tion of data is the right way in or­der to get higher out­puts. Imal men­tioned that the turn­around time for a sam­ple was re­duced to three days from three weeks and the ef­fi­ciency in­crease was recorded at 10 per cent. More­over, the qual­ity de­fects per month also re­duced to half.

man­u­fac­tur­ing pro­cesses, the three im­por­tant areas, apart from safety, that are cru­cial to ap­parel man­u­fac­tur­ing process are Equip­ment, Pro­cesses and Cus­tomer re­la­tion­ship.

The qual­ity of gar­ment highly de­pends on the equip­ment life and its func­tion­ing. Any fault and any dif­fer­ence in the func­tion­al­ity of the ma­chine may hin­der the man­u­fac­tur­ing process and the qual­ity of the prod­uct. The equip­ment main­te­nance can help to in­crease the pro­duc­tiv­ity and ef­fi­ciency to a big level. The fun­da­men­tal ob­jec­tive of main­te­nance is guar­an­tee­ing the qual­ity of the prod­uct made by the ma­chines and ex­tend­ing their work­ing life. “The ma­chines should be con­tin­u­ously mon­i­tored for data col­lec­tion. The fur­ther anal­y­sis of data helps in de­ter­min­ing the equip­ment highly prone to fail­ure and with high main­te­nance re­quire­ment. Also, the data recorded makes a pat­tern for a par­tic­u­lar event. For ex­am­ple when a ma­chine re­quires a part re­place­ment, it may show the same pat­tern of data; analysing the pat­tern, it will be clear about what the pat­tern was for the event be­fore. Based on this, proper ac­tions can be taken for prevent­ing any fur­ther fail­ure that may stop or de­lay the pro­duc­tion,” elab­o­rated Jagdish.

For a more pre­cise and closer pre­ven­tion of fail­ure, the process (Preventive main­te­nance) can be ap­plied to each of the com­po­nent of the ma­chine. Mon­i­tor­ing each com­po­nent of the ma­chine gives one a bet­ter in­sight and helps in the pre­ven­tion of over­all equip­ment fail­ure. There­fore, any change in any com­po­nent when en­coun­tered can be tack­led so that the over­all equip­ment ef­fi­ciency can be main­tained.

“With preventive main­te­nance of each of the com­po­nent, we have been able to boost the OEE (Over­all Equip­ment Ef­fi­ciency) from 66 to 90 per cent,” said Jagdish, fur­ther em­pha­sis­ing that if the steel in­dus­try can achieve this, the gar­ment in­dus­try should also step up to in­crease OEE.

The sec­ond area for data col­lec­tion is the ev­ery­day process and a brief mon­i­tor­ing of these pro­cesses can also help to main­tain the qual­ity con­sis­tency. The hourly in­stead of daily pro­duc­tion mon­i­tor­ing in ap­parel shopfloor can help rec­tify the faults and can help in main­tain­ing the con­sis­tent qual­ity. The end prod­uct should be checked for qual­ity and quan­tity so that any change in that can be ad­dressed to main­tain the con­sis­tency in the next hour. The col­lected data over the process also helps in iden­ti­fy­ing the pat­tern so that it be­comes eas­ier for the Qual­ity Checker to iden­tify the source of flaw for quick han­dling of the sit­u­a­tion. “One of the proven meth­ods of pro­duc­tion mon­i­tor­ing is IoT so­lu­tion which the in­dus­try is still not very re­cep­tive to adopt,” com­mented Jagdish.

En­abling con­nec­tiv­ity be­tween the peo­ple of the or­gan­i­sa­tion can also help in main­tain­ing con­ti­nu­ity in the over­all process. There are a lot of ap­pli­ca­tions avail­able, for ex­am­ple chat bots, that make it eas­ier to con­nect with the peo­ple. The ap­provals and quick queries help the pro­duc­tion, qual­ity

and de­sign teams to han­dle the sit­u­a­tion in the real time it­self. Real time shar­ing of data and pic­tures can pro­vide with the real time in­for­ma­tion that helps with the real time de­ci­sion-mak­ing process. This can help to stop, make changes, al­ter or ad­dress any process at the point of ori­gin it­self, prevent­ing it from ef­fect­ing the end process.

“We have sim­pli­fied peo­pleto-peo­ple com­mu­ni­ca­tion for faster delivery and for deal­ing with qual­ity is­sues and it has given us a pos­i­tive re­sult as 1.28 per cent de­fects in our end prod­ucts have re­duced to 0.3 per cent,” said Jagdish

Cus­tomer sat­is­fac­tion is the ul­ti­mate goal that any com­pany should aim for. There are few main areas that help in achiev­ing over­all cus­tomer sat­is­fac­tion like trans­parency, re­spon­sive­ness, em­pow­er­ment and proac­tive en­gage­ment. To­day ap­parel buy­ers want to know ev­ery sin­gle de­tail of their or­ders for which they have in­vested in. Trust is the big­gest fac­tor no mat­ters how well your prod­uct is; if the cus­tomer does not trust the com­pany he is giv­ing or­ders to, he will look at some other com­pany. “Build­ing trust is not just used for mak­ing new cus­tomers, it is also used for re­tain­ing the cur­rent cus­tomers. Mak­ing the cost and the po­si­tion of the or­der avail­able for the cus­tomers helps in main­tain­ing cus­tomer re­la­tion and also helps in re­ten­tion of the cus­tomers,” stated Jagdish.

Chal­lenges are surely there…

With the ad­van­tages of tech­nolo­gies, there come the chal­lenges as­so­ci­ated with it. The ma­jor chal­lenge dur­ing the im­ple­men­ta­tion of tech­nol­ogy is con­vinc­ing the peo­ple about the use of tech­nol­ogy. Since the ap­parel in­dus­try is more cost­cen­tric where the strug­gle hap­pens more to save cents than dol­lars, the ap­parel man­u­fac­tur­ers some­times do not un­der­stand what longterm ben­e­fits they can achieve by in­tro­duc­ing a cer­tain tech­nol­ogy. The main rea­son is lack of real life ex­pe­ri­ence of theirs. “They want to see a tech­nol­ogy tested by oth­ers be­fore im­ple­ment­ing it in their own fac­to­ries and sites. Till the time they see the profit and think of im­ple­ment­ing, they are al­ready be­hind the lat­est in­no­va­tions and tech­nolo­gies,” em­pha­sised Jagdish.

Se­condly, us­ing the right tech­nol­ogy at the right place and at the right time is still an is­sue. Go­ing dig­i­tal does not mean mak­ing ev­ery sin­gle process dig­i­tal with­out con­sid­er­ing the delivery of it. Crit­i­cal areas should be an­a­lysed for the de­ploy­ment of the tech­nol­ogy. The gar­ment in­dus­try is hu­man­driven in­dus­try, and it largely de­pends on the ef­fi­ciency of the op­er­a­tors. A very good ex­am­ple for main­tain­ing the op­er­a­tor ef­fi­ciency that can be ex­tracted from the steel in­dus­try and ap­plied to the ap­parel in­dus­try is dis­cussed below.

The steel in­dus­try’s end prod­uct is solely re­spon­si­ble for the work­ing of the ma­chines such as dye ma­chines and heavy in­dus­trial ma­chines. While the gar­ment in­dus­try is driven by the sewing ma­chines, which are op­er­ated by the op­er­a­tors. The stitch­ing of the gar­ment also de­pends on the con­cen­tra­tion and ex­pe­ri­ence of the sewing op­er­a­tor. The main fo­cus of the worker eye while stitch­ing a gar­ment should be on the ma­chine nee­dle. The con­cen­tra­tion/ move­ment of the eye­ball of the worker de­ter­mines the op­er­a­tor ef­fi­ciency, but at the same time it is very dif­fi­cult to mea­sure the move­ment of the eye­ball of the op­er­a­tor. Thought should there­fore be given to de­tect the eye­ball move­ment of the ap­parel in­dus­try op­er­a­tors. The steel in­dus­try is al­ready us­ing the tech­nol­ogy used in the trucks go­ing to the ma­jor high­ways, which de­tect the eye­ball move­ment of the driver. When any change is no­ticed, for ex­am­ple, a driver fall­ing asleep or mov­ing in some other di­rec­tion, the man­ager gets the no­ti­fi­ca­tion and im­me­di­ately calls the driv­ers for en­quiry. The same can be ap­plied to the gar­ment sewing ma­chine op­er­a­tor ma­chines but as dis­cussed ear­lier, with ev­ery tech­nol­ogy come the chal­lenges as­so­ci­ated with it. Us­ing this tech­nol­ogy re­quires the will of the op­er­a­tors and the big­gest task is to con­vince them.

The steel in­dus­try is al­ready us­ing the tech­nol­ogy used in the trucks go­ing on the ma­jor high­ways, which de­tect the eye­ball move­ment of the driver. When any change is no­ticed, for ex­am­ple, a driver fall­ing asleep or mov­ing in some other di­rec­tion, the man­ager gets the no­ti­fi­ca­tion and im­me­di­ately calls the driver for en­quiry. Cus­tomer sat­is­fac­tion is the ul­ti­mate goal that any com­pany should aim for. There are few main areas that help in achiev­ing over­all cus­tomer sat­is­fac­tion like trans­parency, re­spon­sive­ness, em­pow­er­ment and proac­tive en­gage­ment. Since the ap­parel in­dus­try is more cost­cen­tric where the strug­gle hap­pens more to save cents than dol­lars, the ap­parel man­u­fac­tur­ers some­times do not un­der­stand what long-term ben­e­fits they can achieve by in­tro­duc­ing a cer­tain tech­nol­ogy.

Build­ing a smart fac­tory

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