A Review on Smart Manufacturing, Technologies and Challenges

International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056

Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN:2395-0072

A Review on Smart Manufacturing, Technologies and Challenges

1Student, JSS Academy of Technical Education, Bengaluru, Karnataka, INDIA

2Student, JSS Academy of Technical Education, Bengaluru, Karnataka, INDIA

3Associate Professor, JSS Academy of Technical Education, Bengaluru, Karnataka, INDIA

Abstract: Smart manufacturing is a technique that enables interconnected machinery and equipment to improve productivity and quality while also optimising energy and working population requirements through the use of big data processing, machine intelligence, and industrial automation technology, as well as their interconnectivity. As a result, both large and small producers must carefully select and prioritise these technologies. Other enhancements may also be required in order to get the most out of the chosen technology. This paper gives a clear picture regarding the implementation of smart manufacturing and also some of the important technologies used here and also the challenges it widely faces. Focusing on agility, production, energy efficiency, and sustainable environmental yields benefits that go far beyond lowering volatility in the market. Creativity, time-to-market, and a speedier, broader study of the trade space are all influenced by agility. The introduction of smart manufacturing and latest technological infrastructure for manufacturers is motivated by all these developments, the factors driving it, and new networkbased computing infrastructure that give unique insights and analysis.

Key words: smart manufacturing; manufacturing; technologies; challenges; automated systems; intelligent manufacturing systems

1. Introduction

One of the most widely used words to define manufacturing in the future is "smart manufacturing. Research about smart manufacturingisbecomingincreasinglypopular.Manyfocusonin-depthcoverageoftheissuesaffectingsmartmanufacturing in order to streamline and organize the increasing amount of research. Since the start of the industrial revolution in United Kingdominmid-eighteenthcenturywiththearrivalofsteamengines,throughallthemassproductionstartingfromtheearly nineteenth century, the commercial potential of electricity,theadvancement of InformationandCommunication Technology (ICT),andtherise ofnewofautomationmachinesintheearlytwentiethcentury,themanufacturingindustry hasundergone innovative progress. Current developments in ICT technologies, such as hardwareandsoftware, are triggering a manufacturing renaissance or revolution. Smart Manufacturing could be the driving force behind the next revolution. It is a collection and approach of numerous technologies that, by combining employees, technology, and information, can inspire significantdevelopmentinthepresentmanufacturingbusiness.Whileprocessimprovementinthe1980sand1990saimedfor costsavingsthroughwasteelimination, SmartManufacturingisa potentialdevelopmentenhancerthataspiresforlong-term growth by managing and improving major manufacturing elements such asproductive output, quality, distribution, and adaptability,basedontechnologyinterconnectionandvariouscomponentsacrosscommunities,humansandtheenvironment. The current era of manufacturing has its roots from lasthalf-century. As software and machine technology has evolved, manufacturing has become more automated. Rather than manual processes, currentmachine equipment’sare mostly controlled by software programmes. Automated material handling systems carry materials and components, which are then placed in automated storage and retrieval systems. Ever since 1980s, different terms have been used to describe automated manufacturing, differing from flexible manufacturing cells and flexible manufacturing systems to computer integrated manufacturingandsmartmanufacturing,dependingontheneedsanddegreeofautomationofashopfloorandtheexecution ofvariousfunctionalmanufacturingsites.Ataboutthesametime,Japanstartedinvestigatingsmartmanufacturing,concluding in the establishment of the Intelligent Manufacturing System (IMS) Program in 1995 to aid industry research. It was understoodthatonecountry'sindustrialindustrycouldnotrestructureonitsown,andthatglobalcooperationwasessential. Large manufacturers from Japan, the United States, Korea, and Europe have started collaborating on the evolution of manufacturing, with Japan leading the way with its most active participants. The Next Generation Manufacturing Systems (NGMS)Program,whichwascreatedasanon-profitorganization,hasbeenresponsibleformuchoftheIMSworkintheUnited States.TheIMSProgramwaslaterexpandedinsmartmanufacturingwhentheEuropeanUnionbeganresearchoperations.

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Even as world moves closer tosmart manufacturing technology, several of the world's most important nations have already disclosedtheirambitionsforthefuturegenerationofcorporations.Industrialrevolution4.0isaGermaninitiativewhichhas beenrecognizedbyalotofnationsasanothersolutionforindustrialgrowth.

2. Components of smart manufacturing

Figure 1-Componentsofsmartmanufacturing

The ideas developed primarily in the realm of computation have been applied to drive smart manufacturing. Manufacturing, on the other hand, will stand to profit from these and many other new innovations. The fundamental foundations will be established by future work, technological innovation, and uses. The final elements could be formalized in a number of methods, include clustering scholarly articles, industrial studies, and knowledge on technological advances utilizing text and data mining technique and algorithms. The six elements of smart factory include manufacturing processes and technologies, resources, information, predicted engineering, sustainable, and sharing of resources and networking. These six elements' names and relative significance have varied over time, but they're always involved in production. Data, for instance, has always been an important aspect of production. In the era of smart manufacturing, it has grown into large amounts of data. Forecastingengineering,whichisbasedonstatisticalanalytics,camebeforeproductionplanningandforecasting.

2.1 Manufacturing technology and processes

Manufacturingtechniquesandimprovementsareexpectedto evolveinthe near future(29).Differentmaterials,equipment, and products will be developed. Additive manufacturing is indeed an example of a modern technology that has changed product design and manufacture, as well as unlocked the way to modern innovations such as bio-manufacturing. Manufacturingmachinery,suchasequipmentthatcan millverticallyandhorizontally,grindandalsodrillhasbeendesigned to incorporate multiple operations. Novel hybrid technologies will emerge, including hybrids of conventional and additive processes, laser manufacturing, and total production. Implementation of various materials, product development, and manufacturing processes will be more prevalent, like the finding of a chemical substance that leads to the construction of a new medication as well as a method of delivery, as well as the production of the medicine and the device. Additive manufacturing would become more common in both small and large firms. A new group of low-cost robots would improve workplace automation. Modernmanufacturing machinery will be substantially highly cognitive of the factory and beyond communicationattributabletosensorsandsoftwarecapabilities.

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2.2 Materials

Smartmanufacturingdoesnotdirectlyurgethedevelopmentofsmartmaterialssuchasshapememoryalloys orfunctionally graded composites. It's feasible that intelligent elements will arise spontaneously. To build innovative product, smart manufacturing can use any sort of material, including chemically synthesized materials and biomaterials. Recovery of materialsfromitemsattheendoftheirliveswillbecomemoreimportant.Landfillscouldpotentiallybecomenewminesfora varietyofcommodities.Somenewmaterialswillnecessitatethedevelopmentandintegrationofnoveltechniquesintosmart manufacturing.Thehuntfornewmaterialsandtheirmixtureswillbegreatlyaidedbyadditivemanufacturingalone.

2.3 Data

Manufacturingisexperiencingadatarevolution.Sensors,wirelessconnectivity,anddevelopmentsindataanalyticsallplayed a role in some of it. Data is gathered from a wide rangeof sources, including several material attributes, process factors, clients,andsuppliers.Thedatawillbeutilizedtodrivepossibledevelopments,suchaspredictivemodeling.Additionally,that willbeaperfectsettingforpreservingandrecoveringhistoricalandmodernindustrialknowledge.

2.4 Predictive Engineering

Amongthemostrecentadditionstotheareaofmanufacturingsolutionswhichmightcontributetoaproactiveandinsteadof reactive business is predictive engineering. In the manufacturing industry, information has typically been used for analysis, tracking, and inspection, like productivityevaluation, process control, and quality management. Six Sigmatechniques and other data-analysis approaches have had such a significant influence on the quality enhancements in industrial goods and services. In contrast, traditional initiatives have sought to look to the past instead of the future of industrial systems and processes.Predictiveengineeringisanewwaytogeneratinglargemodels(virtualrepresentations)ofeventsofinterest.Such simulationswouldpermitforsaidexploringoffuturelocales,manyofwhicharewithinintherealmofpresenttechandothers who have not previously been observed. Today'smodern models will be supplemented with both constrained models (e.g., supply chain behavior) and multi-system modeling (e.g., approaches that combine productivity, quality of products, energy, andlogistics)toassistdecisionsaboutpotentialproductionandmarketconditions.Modelswiththatkindofalargescopecan aidin the restructuring of themanufacturingsector. Some companies may become widelydispersed, and some may become centralized. Productsthatreallyarecost-sensitiveintermsof shipping, duration, orcustomized, for instance,couldbemade neartocustomers.

2.5 Sustainability

Sustainability will indeed be crucial in the industrial industry. The concentration of sustainability initiatives is on materials, productionmethods,energy,andemissionslinkedwithproduction.Everyrealsustainabilitystrategybeginswiththeitemand the market. There would be little question that usingsustainability targets to drive product and processdevelopment yields the greatest sustainability benefits. The below are some such instances:(1) sustainable product design would influence production; (2) sustainable manufacturing techniques will impact product development; and (3) sustainable materials, solutions, and methods will be developed concurrently. The second situation is additive manufacturing, whichhas led touniquecomponentand itemdesignsasa resultofa technique. Sustainabilityisconcerned not justwith whatisproduced, butalsowithhowitisproduced.Itistheimpetusbehindbringingremanufacturing,reconditioned,andrecyclingonparwith production.Thedistinctionseparatingmanufacturingandservicewouldremainblurryduetosustainability.Wayofsharinga useditem,forexample,isnotreallyanormalmanufacturingactivity,yetitmaybeincludedincurrentmanufacturingjargon.

2.6 Resource sharing and networking

As manufacturing becomes more digitized and virtual, most of the innovationand judgmentactivity will take place in the virtual world. Whereasthe digital realmismoreaccessibleattimes,thephysical industrial capital andunderstandingwill be protected.Thisseparationofthedigitalandphysicalenvironmentwillenableforresourcesharingacrossorganizations,even competitors.Serviceandcontract modelshave beenintroducedto themanufacturing business,and where the production of the items is outsourced to other facilities or vendors or third parties. Due to the obviouslyhigh price of innovation, low

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utilization, the level of difficulty, and ambiguity about the usefulness of the new tech, the rapid manufacture (Manufacturing process before 3d printing) emerged decades ago. Shared resource models have proven to be successful, and they are now spreadingbeyondcarpoolingtoincludeUberfortransportationandAirbnbforlodging.Thesetechniqueswillmostcertainly aid smart factoriesby allowing firms to share and make use of manufacturing equipment, software, expertise, and, most importantly, cooperative modelingand innovativespace. While the technicalities of borrowing industrial machinery and distributing software packagesmay be imitated, sharing the creative environment is a challenge. Applying concepts such as MetaandWikitootherelementsofmanufacturingwill takemanydecades.Rather ofrealgoods,allsharingtransactionswill takeplaceinanareafilledwithdigitalmodels.Transport,inadditiontoproductionequipment,isanimportantresourcethat requires consideration. Internal transport, it makes use of specialist material handling machinery or several other stuff like tracks, and physical transport, which supports the supply chain management and distribution chain, which are the primary forms of transportation used in manufacturing [30]. Logistics, in addition to production equipment, is a significant resource thatshould be addressed. There still are two types of transportation in production: internal, whichuses specializedmaterial handling equipment or several lines, and outside, which supports the distribution and supply chain. In the field of manufacturingaccountancy,transportationisfrequentlyregardedasanon-value-addedoperation.Thisleadstothebeliefthat shortening travel distances will not only reduce money but will also have a positive influence on the environment. Through greaterautonomyandcooperation,robotsandself-drivingvehicles(fromthelandtothesky)haveanimpactoninternaland externalindustrialtransportation.Transportationwillplayacriticalroleintransformingthespatialarrangementofindustry onaglobalandregionalscale.

3. Smart Manufacturing Technologies and their roles

3.1 Additive Manufacturing

AdditiveManufacturing(AM),oftenreferredas3Dprintingtechnology,opensupnewopportunitiesforsmartmanufacturing. Customizable, rapid prototyping, generating spare parts rapidly, as well as on manufacturing are all possible with AM technology, which reduces a lot of time and moneyin terms of machinetool maintenance and raw materials.Thesignificant advantageofAMinsmartmanufacturingisthatitsupportsreverseengineeringofalmostanycomponentorproductsusing3d scannerandenablescustomizationindesigningaswellasspeedyduplicationforevaluationandconfirmation.Inadditionto implantation in dentistry and orthopedics for the repair of broken body parts, AM technology is increasingly utilized in medicalscience.AMisusedincivilandarchitecturalengineeringtoprototypeandanalyzesolutionsforcost-effectivenessand satisfactionofcustomers[32-33]

3.2 Artificial Intelligence

Artificial intelligence has been used in the latest generation of manufacturing systems to improve human-robot cooperation and coordination and decrease the number of individuals working in dangerous surroundings, as well as to improve the servicingstructureofthemanufacturingsystemsandidentifyanyerrorsinsidethemachineryandproduct. Self-optimization andautonomous reactionstophysicalchangessuchas altering productionplans,stoppingoroperatinganymachiningunits, autonomous equipment tool replacement, and timely alerting of any unconstrained situations are all capabilities of the artificialintelligencesystem[34-36]

3.3 Virtual Reality

VirtualReality(VR)allowsuserstointeractwithcomputer-generatedgraphicsandfilmsthatsimulaterealworldapplication. VR is wearable equipment with video, audio, location systems like GPS, remote communication to other devices, and technology that allows the user to feel physically present in a virtualized world built in simulations. VR has been used in manufacturing processes to train and educate engineers and technical graduates aboutindustrial processes.VR isutilized in manufacturingstructurestotrainandeducateyoungengineersandtechnicalgraduatesforhandling industrialprocesses.The implementationof VRhasbecomemore effectivethanclassroomknowledgein implementingyoung engineersandtechnical graduatestothemanufacturingmethod,mechanizationprocedures,diagnostics,andmaintenancetechnologies[37-39]

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3.4 Augmented Reality

Computer simulation could indeed be used to generate an artificial experience in the material realm using devices and portablegadgets.Theydeployatechniquethatmixesareal-worldphysicalhabitatwithcomputer-generatedimagestodepict artificially created components to an existing real environment for the objective of training, simulation, or verification of manufacturingmodelsbeforetheygointoproduction.Thiscombinationofvirtualcomputerimagesandreal-worldscenarios aidsintheproduct'simplementationinareal-worldsituation.Whennewworkertrainingandproducttestingareconducted inanartificiallyenhancedenvironmentwithavarietyofscenarios,theyareproventobemoreeffectiveandtime-saving[3941]

3.5 Big Data Analysis

Data gathering and analysis from a variety of sources, ranging fromproduction unit, the business, consumer feedback and product demand systems, and etc, aid in making real-time smart manufacturing decisions. Organizations increasingly desire consumers to share their views and opinions more about products they used and desire to use it because that they may concentrate on producing products that satisfy of a diverse set of consumers. Big data analysis will help the manufacturer describethepresentstateaswellasinducesofproductbreakagesinrealtime,aswellasdrivecustomerstobuyproductsby recognizing their purchasing habits and prerequisites and learning about facts and figures marketing's predictive manufacturinginfrastructure[42-44].

3.6 Cyber Physical Systems

Industrialmanufacturingengineerscansuccessfullysuperviseandmanageproductionprocessviathecomputer,allowingthe controlengineertoaccesstheindustry'smonitoringsystemfromanywhereviacloudtechnology.By utilizingdataprocessing capabilities that really are easily available on the internet, the Cyber-Physical System (CPS) connects quantitative aspects to thephysicaluniverseanditsrecurringmechanisms.TheCPScanalsobedefinedasacloud-basedSCADAsystem,withhigher layers ofsensors,actuators, andhardwarecomponentsanda cyberlayerofprograms,communicationsequipment,anddata transferviatheinternet.CPSiswidelyusedintheaviation,automobile,transport,androadsandbridgesindustries[45-46]

3.7 Flexible and Reconfigurable Manufacturing Systems

Manufacturing mechanism that can adapt to any modifications in built-in priorities and processes as a result of competitive marketdemandsorproductreconfiguration.Theyareconcernedwithcost-effectivenessandtheabilitytorespondquicklyto systemchanges.It canproducesmall batchesandcan be easilyrepurposedto start producinga variety of products.Regular adaptability allows the production facility to produce new types of product in the same production line, whereas machine flexibilityenablestheproductionfacilitytoorganizethemanufacturingschedulesofvariousmachiningstations,distributethe machining activity respectively and automatically start replacing the machining parts. Functionality, adaptability, versatility, flexibility,andmanageabilityarepredeterminedcharacteristicsofFRMSinsmartmanufacturing[47-49].

3.8 IoT(Internet of Things) and IIoT(Industrial Internet of Things)

Smart homes, transportation systems, supply chains, healthcare, agriculture, human pets, and vehicle monitoring apps are examplesofIoTapplications,whereasIIoTconcentratesontheindustrialimplementationofIoT,whichintegratesallmaterial objectsviatheinternet.TheIIoTintegratestangibleitemslikesensors,actuators,andtheentireoperationalsurveillanceand controlsystemtotheinternetcloudintheindustrialworld,enablingeachcomponenttointeractandcollaboratetoachieve a common goal. These interactions between components help with resource, tool, and material optimization, as well as enhanced human-machine interface and smart control systems for resource, tool, and material enhancement. Customerscan also view virtual demonstrations of products, procedures, and industrial plants for marketing and education using the IIoT [50].

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3.9 Simulation

Factory simulations in the virtual environment to optimize machine settings for the earlier production process without evaluatingintherealitywouldsavetime&expenseintheverificationprocess.Followinguponthesimulatedresults,avirtual model iscreated whichmay be used for production strategyandplanning.Additionally,inrecentyears,simulationhasbeen incorporated into SMS systems, which has aided in the examination of design errors, production schedule, manpower, and energy requirements for the entire supply chain, as well as the planning and preparation of cost estimation, profit loss evaluation,andbillofquantitypreparationpriortomovingforwardwiththerealmanufacturingprocess[51-53]

4. Material handling and transport of materials, components, products and people

Material handling and transportation, with lengths ranging from nanometers to kilometers, are essential components of the production chain. Both enable manufacturing and shipping activities to take place across several sites and throughout the world. The movement of items within a facility is referred to as material handling, whereas transportation refers to the movementofitems,parts,anditemsthroughdistributionnetworksthatspandistricts,nations,andnations.Procurementand distribution can account for a significant fraction of the cost of a product; for example, transportation accounts for eight percentofthetotalofthecostofwindenergytower,althoughothercomponentsaccountforagreaterpercentage(e.g.20 %) (Cotrell et al. 2014) [49] Because of the growth of manufacturing, distribution of materials, parts, goods, and persons is expected to be a significant financial element in manufacturing. As a result, workers' transportation and usage expenses for maintaining hardware and software infrastructure across several production locations would be reduced. Job descriptions that are not yet available will be established in order to complete the intelligent production activities. Manufacturing professionalsmaytravelinhugenumbersutilizingvariousmodesoftransportation,suchasvehicles,railways,andflights, in ordertodistinguishtheirgoods.Humanresources,likemanufacturingresources,arepronetobeaffectedinhugenumbers,as mentioned later in this work. The cost of production is influenced by the efficiency with which resources, components, products, and people are transported. Global manufacturing connectivity is built on the foundations of transportation and communication. Transportation is expected to become an essential component of smart manufacturing independent of ownershipdueto:(1)growingdependenceontheflowofresources,parts,goods,andservicepeopledrivenbyindividualized demands, (2) durability, and (3) service levels. Limiting the sustainability consideration to the production envelope would result in a poor solution due to the interconnection of production with supply system exchange. Customer service quality is inextricablylinkedtoinventorylevels,productionresponsetimes,andtransportation.

5. Smart Vehicles

Manyoftoday'sproducttransportationanddistributionvehiclescommunicateandexchangedata.Transportconnectionwill grow because more individuals participate in information sharing, such as automotive communication or automotive centre fordiagnosticsandrepairs.Infact,machinetoolsareexpectedtousethesameinterfaceasconditionmonitoringsystemsand manufacturing.Transportationautomobilesareclassifiedbytypeofvehicle,fuelusage,andtechnologyused.Automotiveare characterized to use any combination of automotive type & technology used. An automobile, for example, may be both independent and rechargeable. Product handling equipment, private automobiles, trucks, and public transportation are all affected.Technologyappearstobenaturallyevolvinginthedirectionofcombiningthenotionsoftransportation,energy,and sustainability.Technologyappearstobenaturallymovinginthedirectionoftyingtransportation,energy,andsustainabilityto production.For example,anelectricforklift,a vehicle,a lorry,oralong-journeytraincouldallbeself-driving.Vehiclescould also be grouped together. Electric car batteries have previously been charged using power produced by conventional renewableenergypowerplants.Vehicleswillbebuiltforlong-termdurability,featuringfuelefficiency,andwillrunonpower producedfromrenewablesourcesasturbinesorgas.Amorefuel-efficientvehiclewillneedlessmaterialandhaveageometry thatisshapedtoreduceairresistance.Whenitreachesthedeclinestage,themajorityofitscomponentswill bereprocessed andreprocessed[45].Topicofdependableelectricvehicledesignhasgottenlittleattentiontodate.Perhapsthecarindustryis undulyfocusedongaininga footholdintheindependentmarket.Vehicleaccessibilityisatopicthathasbeendiscussedfora long time. In the domain of public commuting, it has a long history. In the mass-transit domain, it was implemented in two ways:physicalanddataconnectedness.Atrainisamechanicallyconnectedautomotivethatcommunicateswirelesslyorover thecables.Traditional connection advantagesmay beapplicabletothe next era of automobilesand goodshandlingsystems. Vehicles,likeindustrialmachinery,canbeconnectedbothonlineaswellasoffline.Thedigitalconnectioncanbeestablishedin

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arangeofmethods,fromautomotive-to-automotivecommunicationtotrafficcontrol.Thedevelopmentofconnectedvehicles has resulted from advancements in transportation productivity, efficiency, and safety. The advancement of transportation productivity, efficiency, and safety has led to the development of connected vehicles. For example, in the same way that one operatormaycontrolseveralmachinesinmanufacturing,havingonedriverforalargenumberofvehiclessavesmoney.Inthe personal-vehicle arena, the concept of shared mobility has been around for a long time. The benefit for using shared transportation was usually access to a less congested highway lane. The vehicle's owner is usually one of the passengers. Transportationforsmallgroups(e.g.,sixtotenpersonsinavan)tolargegroups(e.g.,amasstransitsystem)isa well-establishedtechnique.Usingourownvehicleforpersonalmobilityisinefficientintermsofbothenergyand cost.Personalvehiclesaretypicallyunderutilized.Wedon'tthinkthatway,though,whenwhatwereallyneedisa transportationservicethatdoesn'trequireustobuyacar.Subscribingtothetransportationserviceideaallowsfor better vehicle utilizationand lower transportationexpenditures. As a resultof the increasing use, the number of automobilesontheroadisreduced,whichhasagoodinfluenceontrafficcongestionandtheenvironment[45].

6. Smart Manufacturing Systems challenges

Although smart manufacturing technologies can handle a broad number of risks and difficulties faced by established companies, there are still a few hurdles to overcome during their deployment. Safeguards, a lack of systems development, a lack of return on investments in research and development, and financial problems are assumed to torment smart manufacturing systems during in the construction of the new production technology or the upgrade of existing businesses with smart manufacturing technology, according to various totally reliant variables. The sections that follow look at the challengesthatsmartmanufacturingtechnologiesconfront,aswellaspossiblesolutions.

6.1 Security Concerns

The usage of a network system which is integrated in a production system for transferring data among production or processing units and end consumers is referred to as a smart manufacturing system. It requires network access for this purpose,whichisarrangedmostlythroughtheinternet. Dataandinformationsecurityarerequiredatmultiplestagesacross the system when transferring data over the internet, including world - wide unique identification and end-to-end data confidentiality. As a result, each network component should be safeguarded against attacks from the outside and data theft. When developing network infrastructure, such as smart manufacturing technologies, the most important aspect is to ensure thedevice’sandoverallnetwork'ssecurity[46].

6.2 System Integration

Synchronization of modern technological devices with existing devices is another barrier in implementing a smart manufacturing system. Connectivity concerns between existing and new devices create a wide range of problems for smart manufacturing technology usage. New gadgets may employ a different protocol than old gear controlled by specified communication standards. Additionally, for machine-to-machine communications and system integration, more communication is required. In order to link more devices at the same time, IPv6 connection is essential in modern manufacturingprocesses[39]

6.3 Inter-Connectivity

Interconnectivity refers to a system's ability to understand and access the features of another system independently. This functionality allows them to exchange data and information despite of the hardware or software they use. Industry 4.0 has fourdegreesofconnectivity:operational,systematical,technical,andsemantic.CPSandIndustry4.0arelinkedbyoperational interoperability, which raises questions about Industry 4.0's conceptual structure. Standards, recommendations, principle techniques, and models are all concerned with systematic interoperability. Technical interoperability defines tools and platforms for the technical and ICT environment, as well as related software. Information sharing across various levels of organizations and individuals is the subject of inter-connectivity. If communication techniques and rules are not correctly matched,interconnectionmaynotevenbepossible.Thesystem'sinter-connectivityrestrictionsaredeterminedbyvariations

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6.4 Safety in human-robot collaboration

Arobotorlightweightrobot;isatypeofrobotthatcaninteractwithhumansintheworkplaceinasafeandphysicalmanner, as well as collaborate by incorporating innovative methodologies from human-machine interaction (HMI) [53]. The International Federation of Robotics is a non-profit organization that promotes robotics around the world. Human-robot collaboration is defined as a robot's ability to work in tandem with humans in an industrial setting to complete complex operationsthe main focus must be on the occupational health and safety of individuals who work on the workplace; any potentiallydangeroussituationmustbeavoided,andessentialoccupationalsafetyshouldbemaintained [14].Whenadopting theCPSframeworkorindustrialroboticsystems,themainfocusshouldbeonminimizinganymechanical,electrical,thermal, noise,vibration,radiation,andworkenvironmentdangersintheworkplace[11].

6.5 Humans in smart factories

The field of human-robot collaboration (HRC) has recently attracted a lot of interest. Many research and professional institutions across the planet are exploring with human-robot collaboration. One of the key reasons is the increased use of robots. Robots are regarded to offer alternatives to several of modern social concerns (e.g., providing care, substituting humans in hazardous tasks).The framework for human-robot collaboration is shifting beyond separate human-robot interaction (in the past) to increased human access to machines (in the present) to close human-robot interaction (future). Anotherkeyconcernwiththedeploymentofrobots,particularlyinambiguoussituations(thatis,outsideofdistinct,guarded zones),isthelackofreliablesensors.Sensorinformationisrequiredforarobottoperformtaskssuchasresponsiveplanning, movementcontrolling,visualservoing,defectdiagnostics,andsafetylevelmaintenance.IftheHRCequipmentisintendedfor unorganized areas with unexpected human mobility, it must be equipped with a flexible sensor system that includes range, proximity, touch, vision, sound, temperature, and so on. Human-robot interaction will boost the versatility of automated industrial applications still further. Procedures will be enhanced by augmenting human cognitive and sensorimotor abilities withrobotaccuracyandfatigue-freework.Theseapproachesdonotnecessitateasafeplacefromaroundrobots,oreventhe safetyzonesarelessthanthoserequiredforregularrobots.Theintuitivedesignoftheinterfaceandoperationoftherobot,as wellastheworkinstructionsbetweentheoperatorandrobot,isacriticalaspectforsuccessfulHRC.

6.6 Robots in smart factories

Robots in smart factories are equipped with sensors to enable for human-robot collaboration in a secure work place. When comparedtoconventionalrobots,so-calledmachines(cobots)havevariousadvantages.Theserobotsarehuman-safeandwill provide the space needed by regular robots, that need a protective barrier. The safety features can be a mixture of different technologies, and the use of sensing devices to slow down the robot when individuals approach; force constraints to reduce threats to people or the environment; and the ability to detect human intent and maneuver accordingly. Aside from these safetyprocedures,severaltypesofhuman-robotcollaborationcanbeapplied.Humansexecuteactivitiesthatrequirethemost finesse, whereas robots perform repetitive, heavy, and boring ones. According to ISO 10218-2, a collaborative robot is classified as "a robot built for directly interacting with a person within a predefined collaborative workspace, i.e., work area within in the secured environment in which the robot and human can accomplish tasks at the same time during production operation."Theprimarypremiseisthatrobotsdonotharmpeople,andthetoolstosafeguardpeopleareregulatedforceand velocity,separatedmonitoring,hand-guiding,andasafety-ratedmonitoredhalt.

6.7 Multilingualism

Smartmanufacturingsystemsshouldbeabletomanagemultilingualoperationsbytranslatinganyinputsprovidedinhuman language into machine language and instructing the machine to do the necessary operation [58]. It must be able to take commands directly from the controller, whether in speech or text format, to make smart manufacturing a reality and to combinemachinelearning,artificialintelligence,andsophisticatedtechnologiesintomanufacturingsystems.

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6.8 Return of Investment in New Technology

When transitioning to a better technology in an established industrial system, the economic assessment and return on investmentarecarefullyexamined.Theadditionalcost ofimplementingcurrenttechnologyisoffsetbymanufacturinglosses throughoutthecourseofanupgrade,andthetimeittakestorecoupthecapitalwithexistingframeworkincomedetermines theacceptanceofnewertechnology[50]

7. Smart Manufacturing Systems

Many studies have extensively identified a number of Smart manufacturing(SM)-related characteristics, technologies, and enablers.Someoftheseattributes,technologies,andenablershavebeenmentionedspecifically.Moreover,becausethisisnot alwaysthecase,theauthorsconductedathoroughreviewoftherelevantmaterialtoidentifyextraproductsthatcanbelinked with these categories. Smart Manufacturing Leadership Coalition(SMLC)has proposed some SM platforms that take into account the integration of various technological advances in the system. The vertical and horizontal connectivity of manufacturing systems at the plant level is what SM is all about. As a result, an SMS should be aware of the status of its forerunners, successors, and parallel machines. In the literature, a computational-based learning system that integrates networkeddata,integratedautomation,andintelligentinformationhasbeenusedtoconstructSmartManufacturingSystems (SMS). The SMSs' scope is, however, confined to calculation in this situation. The (National Institute of Standards and Technology) NIST has presented a strategy model for SM that emphasizes agility as a goal and may be applied to different objectives.ThecategorizationofSMSwasbasedonthreemeasurements:agility,assetutilization,andlong-termviability.Other traits and technologies have been utilized to characterize SM in the same way. There are four steps to SM: (1) create areas wherechallengedescriptionscanbeaddressed,(2)establishcyber-platforms,(3)datasharing,and(4)implementSM-friendly regulations.Thereis,however,noresearchthatprovidesafulllistofqualities,technology,andenablingvariablesthatdefinea "smart" manufacturing system. The qualities, technology, and enablers that must be included in an SMS will vary. Enabling TechnologiesforSmartManufacturing:KevinAshtonoriginatedtheterm"internetofthings"in1999.TheInternetofThings (IoT)isahugenetworkoflinkedthingsthatisexpectedtoconnectapproximately20.8 billiondevicesby2020.It'soneofthe keyenablingtechnologiesforIndustry4.0andSmartManufacturing.TheInternetofThings(IoT)isanetworkofthingssuch as software, sensors, electricity, and physical objects. General Electric introduced the Industrial Internet of Things (IIoT) in 2012. (IIoT). Deep learning and big data, as well as sensor data and automation, are all used in IIoT to apply IoT to manufacturing.

The phrase "cloud computing" was coined in 2006 to describe the delivery of computing services such as servers, storage, databases, networking, software, analytics, and more via the internet. Companies profit from CC because of its versatility, multi-tenancy, reliability, scalability, and other features. Professor Bo Hu Li invented the term "Cloud Manufacturing" (CM) in China in 2009. Manufacturing is referred to as CM. CM is a customer-centric manufacturing process that allows you to access a common pool of manufacturing resources on demand to improve efficiency and lower product lifecyclecostsinresponsetochangingcustomerneeds.Everymanufacturingresourceissensedandconnectedtothecloudin CM.IoTtechnologysuchasRadiofrequencytagsandbarcodescanbeusedtoautomaticallyshareandexchangedata.

Lee et al. (2014) (23) the term "cyber-physical system" (CPS) was coined by the National Science Foundation in the United States in 2006. CPS is focused with the structure and operational attributes of software controlled systems, whereas IoT is concerned with internet connected physical devices. The majority of studies linking CPS to SM have proposed a 5C designofCPSforSM,withfivelevels:smartconnection,data-to-informationconversion,cyber,cognition,andconfiguration.

Smart Manufacturing and related issues: Lu et al. (2016) [22] "Smart Manufacturing is the capability to resolve present and future problems using an accessible framework that enables solutions to be adopted at business speed while providingfavouredvalue,"accordingtotheSMLCdefinition.

TheSMEcosystem,SMcapabilities(productivity,agility,quality,andsustainability),andSMstandardsprospectswere examined, proposed a structure comprising four components as a data-driven strategy for SM (manufacturing module, data driver module, real time monitor module and the problem-solving module). Manufacturing benefits from a data-driven approachsinceitboostsproductionefficiencywhilealsoincreasingproductperformance.

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TheworldhassteadilydriftedawayfromSMinthelastdecadeortwo.Because ofthevarioustrans-disciplinarybenefits of SM, research and development in the manufacturing area employing CC and IoT applications has risen significantly. The majority of SM research and development has been concentrated on one specific element of manufacturing. A few of the researchers developed a framework, while others proposed architecture for a future SM system. Many successful initiatives weretriedonexperimentallevelsfromthestandpointofexecution.Thefollowingresearchgapshavebeenidentifiedbasedon aliterature review:(1)theindustrialuseofSMisstillinits earlystagesandit needstobethoroughlytestedinalarge-scale setting. (2) Although SM is becoming better known, it is still limited to SMEs. (3) For SM service, the usage range and geographical location are critical. (4)Manufacturers are also concerned about connectivity and scalability. (5) Additive manufacturingisthoughttobeabetterfitforSMadoptionthansubtractivemanufacturing.

8. The future of smart manufacturing

Industry4.0hasbothadvantagesanddisadvantages.Acceptanceofthenewmanufacturingrealityandtransformationmay be the most difficult obstacle. The next generation of low-priced artificial intelligence can support a replacement wave of trade automation. This alone can lead to the creation of latest 'cyber' jobs as critical ancient jobs. It is always difficult to changetheconversionfrombluecollaremploymenttowhitecollar.The"cyber"componentofthesmartfactoryisaseparate business,withjobstobecreatedanda stafftobe educatedby educational institutions.Smart enterprise willwork betterif we have a better understanding of future needs (Kusiak 2017b) (59). The transition from today's manufacturing to tomorrow's manufacturing is a massive undertaking due to the unpredictability of the market and technology, hardly any businesscanbeeffectiveinaccomplishingallresponsibilitieson its ownandsmart manufacturingisevolving,aswellasits components will become apparent in the next few years. The following ten theories indicate some of the features of upcomingproduction.Eachpresumptionissupportedbyabriefexplanation.Thehypothesesareintendedtoencapsulatethe essenceofintelligentmanufacturing.Someofthemcouldbeproved,ismuchless relevant,andevenberemovedovertime, whereasothersevolveintonewtheories.

8.1 Digitalization of manufacturing

Manufacturing will become increasingly reliant on data, needing the collection of additional data.Many manufacturing industriesarealreadymakinggreateruseof data.For example,the windenergysectorhasadoptedsupervisorycontrol and dataacquisition(SCADA)devicesthatcollecthugeamountsofdataonprocessvariablesfromwhichmanufacturingmaylearn. SCADAtechnologymakesitsimpletocollect,store,andexchangeprocessdata(Kusiak2016b)[57].

8.2 Growth based on simulation, optimization, and modelling

Thegrowingsizeofthedatainindustry4.0(Hypothesis1)willalmostcertainlyresultinthedeliveryofproductsandservices from the input data. Information representations will be increasingly popular since they enable the incorporation of factors from several domains (for ex, goods, service, and transportation) in simulations which would be difficult to construct using conventional methods e.g.Mathematical models. Fluid estimation methods will be widespread in smart manufacturing. Predictivemodels,aswellasvirtualandaugmentedreality,willbecomemainstream[35]

8.3 The phenomenon of materials, products, and processes

Thenumberofoccurrencesinwhichanewmaterial,procedure,andproductarealldevelopedatthesametimewillincrease. Someofthemostinnovativeideasinthepastoccurredwhenamaterialandaprocedureweredevelopedatthesametime.The advancementofmaterials,methodsandproductsisexpectedtoleadtoinnovationsinthefuture[8]

8.4 Physical assets and cyberspace can be separated vertically

The physical layerand the logistic layer in manysmart organizations will be designedfor easeandspeedofconnecting and disconnecting from one another. The vertical reparability will be largely ascribed to the necessity for physical asset reconfiguration.Newsystemarchitectureswillemergeasaresultoftheincreasedhavetofurthermeetshiftingdemands,new system architectures will arise, which will be supported by rising digitization and standardization. The ease with which the physicalandcyberlayersofacompanymaybeseparatedverticallywilldefinethefuturearchitecture.

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8.5 Enterprise dichotomy

Contrasting cloud computing market models are likely to arise: being with strongly integrated assets and services, or one witharchitecturalseparationbetweenthetwolevels Reasoning:InaccordancewithHypotheses3and4,strongdirectional connectivityordirectionalreparabilitydesigns(adichotomy)mayemerge[4].

8.6 Horizontal connectivity and interoperability are becoming more important

Smartmanufacturingbusinesseswillhavegreaterhorizontalinformationexchangeand connectivity.Thiswillbeprompted by the need to reorganize physical and logistical assets both within and between businesses. In both tiers, standardization will act as a facilitator. The growing amount and pace of information coming through a contemporary company will eventuallydrivetheadoptionofservicesthataddressenhancedhorizontalinformationexchangeandconnectivity[15]

8.7 Resource sharing

Production and transportation assets would be exchanged throughout manufacturing chains on a regular basis. The unprecedented lateral interconnectedness of clever firms paired with price movements would allow sharing of manufacturingequipment,transportation,andotherresources[23]. Organizationsmayacquiretechnologywiththeexpress assumptionit'dbeexchanged,whichmightaidinthedevelopmentofindustrialequipment.

8.8 Autonomous equipment monitoring, diagnosis, and repair

Equipment problem analysis and forecast can become commonplace in industrial automation. In some circumstances, restore may be possible. Equipment monitoring creates data that is used to support diagnostic models that are used to evaluateandforecastthestatusofdevicesandfacilities.Itwillbecomeroutinepracticetopreventproblemsfromhappening andtopredictfuturefaults.

8.9 Collaboration and standardization

Collaborativestandarddevelopmentcanorganicallyevolvethatsuittherisingdemandsoforganizationalcommitmentand interdependence. The demand for standardization and coordination will be fueled by the increasing dependency on data, resourcesharingandtheneedforverticalreparabilityandhorizontalconnectivityandinteroperability.Duetothedifficulty ofthechallengesathand,collaborationwillprobablycertainlyimprove[34].Metricstandardsthatdemonstrateacompany's competenceforhorizontalandverticalconnectivityandinteroperabilitywouldbebeneficial. Acompanymaybeassigneda classbasedonthesequalities;forexample,aClass4(outoffiveclasses)firmmightreadilydobusinesswithanyotherClass 4orlowerfirm.Organizationswitchingandinteroperabilitywouldbesubstantiallyimprovedwithsuchastandard.

8.10 Cyber security and safety

Cyberprotectionwillremainaconcernthatmustbetackledonaregularbasis.Growingdatavolumesanddependencymake cyber security critical to industry. Advances in Industry 4.0, as well as increased data volumes and reliance, make cyber securitycritical.AdvancesinIndustry4.0andtheEconomy[6].Thisisparticularlyessentialbecauseinformationsystemsare becomingamorerelevantdeterminantofacompany'smarketvalue.Thenecessityofhumanandmachinesafetywillgrowas automation and system autonomy increase. Equipment and radar will become increasingly important. In reality, the similaritiesbetweenequipmentdiagnosisandcybersecuritysolutionscouldbeinvestigated.

8.11 Need of smart manufacturing transformation

A potential approach of boosting the productivity of the industrial revolution is large-scale collaboration on the primary concerns related to the industries with the largest social implications. The construction of an accessible software platform embracing key industries could facilitate such collaborations, including the development of data-driven models. Without a

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doubt,publicplatformswillberealizedatdiversescales.Instudyonjointmanufacturingnetworks,thesignificanceoftoolsin joint international projects has been demonstrated. Increasing the scale and scope of collaborative modelling work, on the other hand, makes the effort worthwhile. In every collaborative effort, considerations of trust and information transparency mustberesolved[54]

Gaining better insights into trust on smaller platforms will be the firststep towardsaddressing sharinginformationand expertise.Tobringsmallandlargebusinessestoaunifiedplatformforcollaboration,modellingatmultiplescalesisessential. It is critical, in fact, to ensure that small and medium-sized enterprises are seated simultaneously as large corporations. Aroundtheworld,theextenttowhichsmallandmedium-sizedbusinessesareactiveindesigningtheenterpriseofthefuture differs. Whilesmall businessentrepreneurshipprogramsare moreprevalentintheUnited States,Asia andEuropeshoweda stronginterestinsmallbusinessdifficulties[54].

9. Conclusion

Automated manufacturing was planned and proven decades ago. The industry has shifted away from pursuing the ideal of 100% automation for sound business reasons. Without a doubt, some smart factories will be highly automated. Smart manufacturing, on the other hand, is about the manufacturing firm's independence, development, simulation, and optimization,notthelevelofautomationonthefactoryfloor.Thescopeandtimespanofthesimulationandoptimizationwill bedictatedbythedataandtechnologyavailable.Thelevelofsmartnessofanorganizationstandswillbedeterminedbyhow well the physical sector has been mirrored in virtual worlds. This article presents a smart manufacturing vision. Its essence was concentrated in six components that set it apart from traditional production. Ten hypotheses describing smart manufacturingwereusedtosupportthecomponents.

10. Declarations:

Funding: Allauthorscertifythattheyhavenoaffiliationswithorinvolvementinanyorganizationorentitywithanyfinancial interestornon-financialinterestinthesubjectmatterormaterialsdiscussedinthismanuscript.

Conflict of interest:Theauthorshavenoconflictsofinteresttodeclarethatarerelevanttothecontentofthisarticle

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About Authors

PratheekMGouthamisanundergraduateMechanicalEngineeringstudentatJSSAcademyofTechnical Education. His areas of interests are Manufacturing, Engineering Management, Automotive and Aeronautical.

RohitYRisanundergraduateMechanicalEngineeringstudentatJSSAcademyofTechnicalEducation. HisareasofinterestsareManufacturing,Materialscience,andoperationsmanagement

Dr. T S Nanjundeswaraswamy is Associate Professor, Mechanical Engineering Department, at JSS Academy of Technical Education, Bangalore, Karnataka, India. His areas of expertise include Probability and Statistics, Simulation Modeling, Operations management, human resource management and organizationalbehavior.Hehasmorethan15yearsofteachingandresearchexperience.