Digital Factory Pilot Line

Distributed intelligence systems are based on the use of cooperative systems, organized in hardware or software components, that independently handle specialized tasks to achieve system-level goals and a high degree of flexibility. Industrial edges allow data produced by sensor-rich assets like machines, equipment and devices, to be pre-processed in real-time, merging industrial IoT data with operational data. Companies can also take advantage of a Cloud system where it is possible to extensively process the aggregated data, execute critical actions and develop AI-driven business intelligence logics.

Exten­ded rea­li­ty (XR) repre­sen­ts the mixture of aug­men­ted rea­li­ty (AR), vir­tual rea­li­ty (VR) and mixed rea­li­ty (MR) tech­no­lo­gies, whi­ch tac­kle various manu­fac­tu­ring domains such as trai­ning, edu­ca­tion, security and simu­la­tion. Thanks to com­mer­cial­ly avai­la­ble hard­ware, the manu­fac­tu­ring indu­stry has seen an increase in the use of advan­ced XR tech­no­lo­gies, shor­te­ning the gap bet­ween 3D modelling and vir­tual envi­ron­ment crea­tion. Tech­no­lo­gies such as holo­gra­phic viewers, vir­tual glas­ses, smart glas­ses and smart hel­mets, beco­me items to design vir­tual simu­la­tion environments and improve the operator’s functionality, impacting the manu­fac­tu­ring busi­ness para­digm itself.

The adoption of indu­stry 4.0 tech­no­lo­gies brings new cyber risks to the ope­ra­tio­ns and to the busi­ness itself. Because of the interconnection of smart fac­to­ry tech­no­lo­gies, cyber threa­ts are frequent and expo­se peo­ple, tools, phy­si­cal pro­ces­ses, and intel­lec­tual pro­per­ty to a high risk. The game has chan­ged: in the past, cyber­se­cu­ri­ty aimed at pre­ven­ting only the con­nec­tions between external and internal areas; today, with machi­nes con­nec­ted to the cloud, cyber­se­cu­ri­ty aims at gua­ran­teeing a ver­ti­cal, acti­ve and exhau­sti­ve IT/ OT pro­tec­tion.

All around the world, manu­fac­tu­ring indu­stries con­stan­tly try to impro­ve their pro­duc­ti­ve per­for­man­ce. Lean Pro­duc­tion and World Class Manu­fac­tu­ring are the most popu­lar stra­te­gies that com­pa­nies adopt to boo­st their pro­duc­tion effi­cien­cy, and they can be implemented not only by big enterprises, but also by SMEs and other realities. Digi­tal tech­no­lo­gies sup­ports the adop­tion of tho­se effective prac­ti­ces, both in the pro­cess desi­gn pha­se and at an ope­ra­tio­nal level.

Pre­dic­ti­ve main­te­nan­ce aims at using data ana­ly­sis tools and tech­ni­ques to detect ope­ra­tional ano­ma­lies and pos­si­ble equi­p­ment defec­ts, in order to fix them befo­re the actual fai­lu­re. Pre­dic­ti­ve main­te­nan­ce allo­ws to reduce the fre­quen­cy of maintenance services as much as pos­si­ble, pre­ven­ting unplan­ned repairs and costs. However, it requires to defi­ne a com­plex plan which deals with data acqui­si­tion, data aggre­ga­tion, cyber­se­cu­ri­ty, and data mana­ge­ment poli­cies. It inclu­des desi­gning sophisticated logics and instru­men­ts, as well as the pro­per user inter­fa­ce to sup­port main­te­nan­ce staff in efficiently per­forming their job.

The con­cept of next generation net­works is based on enabling exten­si­ve and distri­bu­ted broad­band net­works to con­nect com­pa­nies and sho­p­floors. Inco­ming mobi­le wire­less con­nec­ti­vi­ty, like 5G and WiFi6, will boo­st con­nec­tion speed, impro­ve­ bat­te­ry life, increa­se net­work capa­ci­ty and enlarge the band­wid­th with respect to pre­vious gene­ra­tions net­work. When it comes to Indu­stry 4.0 use cases, it will faci­li­ta­te the adop­tion of ultra low-power IoT sen­sors, low laten­cy for impro­ved XR and real-time loca­tion ser­vi­ces (RTLS).

Adop­ting Indu­stry 4.0 is not always related to huge invest­ments or manu­fac­tu­ring greenfield: most of the times, it means iden­ti­fying and applying the pro­per digi­tal COTS avai­la­ble tech­no­lo­gies, allowing for example to gather data whi­ch can then be used to inform deci­sion-makers in real time. It is about taking small steps, stu­dy­ing the bro­wn­field and the spe­ci­fic com­pa­ny needs, avoi­ding rede­si­gning equi­p­ment or pur­cha­sing expen­si­ve appa­ra­tus. It is about eva­lua­ting value added, because pro­duc­tion effi­cien­cy is the dri­ver to tac­kle the com­pe­ti­tion.