Visualising design problems using digital twins

Whether you con­sid­er wind tur­bines to be majes­tic struc­tures or a blight, there is no deny­ing that they’re an effi­cient way of pro­duc­ing ener­gy. But what’s not so effi­cient is there’s a knowl­edge gap between their design and the oper­a­tions and main­te­nance (O&M) stage. 

The aver­age wind tur­bine requires main­te­nance check-ups two to three times a year and its lifes­pan is about 20 years or more, depend­ing on envi­ron­men­tal fac­tors. 

Inspect­ing and main­tain­ing wind tur­bines can be extreme­ly dif­fi­cult, espe­cial­ly if they’re off­shore or in remote loca­tions, where engi­neers can face wind and vis­i­bil­i­ty issues. 

In addi­tion, sched­uled main­te­nance can often lead to poten­tial defects being over­looked, which then leads to fur­ther unsched­uled and reac­tive main­te­nance. A study by aca­d­e­mics in the UK and Ger­many has sug­gest­ed 25% of wind tur­bine faults can be respon­si­ble for up to 95% of down­time.  

Dig­i­tal twins have the poten­tial to change off­shore wind man­age­ment and bridge the dis­con­nect between the design and O&M stages. 

By cre­at­ing a dig­i­tal rep­re­sen­ta­tion of a phys­i­cal asset, engi­neer­ing teams can mon­i­tor the oper­a­tional per­for­mance and health of the asset through real-time data col­lat­ed by a net­work of sen­sors. Using machine learn­ing, the dig­i­tal twin con­tin­u­ous­ly updates to reflect the real-time work­ing con­di­tion of the asset. 

Engi­neers can be alert­ed to poten­tial defects and car­ry out main­te­nance before a fault occurs. This pre­ven­tive approach to main­te­nance can low­er costs and reduce down­time. 

The insight gleaned through the data can also give oper­a­tors a bet­ter under­stand­ing of how a wind tur­bine is per­form­ing and is expect­ed to per­form over the rest of its life cycle. 

This infor­ma­tion can then be fed back to man­u­fac­tur­ers who can then tweak designs, using gen­er­a­tive design soft­ware to opti­mise the lifes­pan of future wind tur­bines. This, in turn, can result in a supe­ri­or prod­uct as it takes the drudgery out of the design process and enables man­u­fac­tur­ers to focus on deliv­er­ing the best pos­si­ble out­come. 

An exam­ple of dig­i­tal twins in action is GE’s dig­i­tal wind farm. Cloud-based mod­els mon­i­tor and opti­mise the per­for­mance of tur­bines as they con­tin­ue to run and gen­er­ate ener­gy. GE has demon­strat­ed the tech­nol­o­gy can help to increase pro­duc­tion by around 20% and cre­ate an addi­tion­al $100m in rev­enue over a turbine’s life cycle. 

It’s a growing digital twins market

Dig­i­tal twins aren’t a new kid on the IoT block. As with any tech­nol­o­gy with a fan­cy name, there has been a buzz around it for a num­ber of years. Broad­ly speak­ing, though, the true poten­tial and appli­ca­tion of dig­i­tal twins is yet to be ful­ly realised.

Accord­ing to ana­lysts at Research and Mar­kets, the dig­i­tal twin mar­ket will grow at a com­pound annu­al growth rate (CAGR) of 41.7% between 2021 and 2027, by which time it will be val­ued at $63.5bn. Adop­tion of dig­i­tal twins will only gath­er pace as more com­pa­nies and indus­tries embrace Indus­try 4.0 tech­nolo­gies, the research notes. 

While pre­dic­tive main­te­nance and per­for­mance mon­i­tor­ing appli­ca­tions are expect­ed to dom­i­nate the mar­ket, busi­ness opti­mi­sa­tion appli­ca­tions are fore­cast to see a CAGR of 42.2% through 2027. Inven­to­ry man­age­ment appli­ca­tions are expect­ed to grow at a rate of 42.7%.  

Adop­tion of dig­i­tal twins is being accel­er­at­ed by the Covid cri­sis, with IoT tech­nol­o­gy being used to mod­el the post-pan­dem­ic recov­ery. Dig­i­tal twins can help man­u­fac­tur­ers to eas­i­ly iden­ti­fy poten­tial defects with designs that could cause sup­ply chain bot­tle­necks fur­ther down­stream. 

“As they emerge from the pan­dem­ic, com­pa­nies should be con­sid­er­ing using dig­i­tal twins to bet­ter pre­pare for unex­pect­ed shocks and to build an intel­li­gent and resilient ecosys­tem,” says Andrew Dun­can, part­ner and UK coun­try head at Infos­ys. The glob­al IT con­sul­tan­cy teamed up with GE in 2015 to devel­op the world’s first dig­i­tal twin for air­craft land­ing gear.

Many small­er com­pa­nies still rely on lega­cy sys­tems and out­dat­ed appli­ca­tions, while there’s a moun­tain of tech­ni­cal debt that needs to be culled, he says. 

If man­u­fac­tur­ers want to com­pete in an increas­ing­ly com­plex and dig­i­tal world, Dun­can adds, “it’s more impor­tant than ever that they review and upgrade lega­cy core sys­tems to sup­port the agili­ty and inno­va­tion which fuel dig­i­tal trans­for­ma­tion”.

Better connectivity leads to better designs 

Fail­ing to mod­ernise lega­cy sys­tems and embrace Indus­try 4.0 can be prob­lem­at­ic. Even if a man­u­fac­tur­er is using dig­i­tal twins and gen­er­a­tive design soft­ware to opti­mise pro­duc­tion, a sup­ply chain can be brought to a screech­ing halt by a sin­gle stake­hold­er not lever­ag­ing data.

Although some man­u­fac­tur­ers may be resis­tant to new tech­nolo­gies, IDC isn’t expect­ing this to be too much of an issue. Sev­en in 10 respon­dents sur­veyed by the glob­al mar­ket intel­li­gence firm have iden­ti­fied dig­i­tal twins as an impor­tant strate­gic ini­tia­tive going for­ward. 

What’s more, IDC research has fore­cast that 65% of glob­al man­u­fac­tur­ers will see sav­ings of 10% in oper­a­tional expens­es by 2023. And as dig­i­tal twins con­tin­ue to advance, thanks to IoT and machine learn­ing, man­u­fac­tur­ers will only get more val­ue out of the tech­nol­o­gy. 

Emerg­ing tech­nolo­gies, such as edge com­put­ing and 5G wire­less con­nec­tiv­i­ty, will fur­ther enhance the capa­bil­i­ties of dig­i­tal twins, enabling even faster deci­sion-mak­ing.

That said, the more IoT devices there are in man­u­fac­tur­ing oper­a­tions, the more oppor­tu­ni­ties there will be for cyber­crim­i­nals and hack­ers to exploit. For this rea­son, it’s impor­tant that man­u­fac­tur­ers have robust cyber­se­cu­ri­ty strate­gies in place.

“Secu­ri­ty teams need to col­lab­o­rate with C‑suite lead­ers to ensure cyber­se­cu­ri­ty deci­sions sup­port the company’s strate­gic goals,” says Dun­can. “It’s absolute­ly vital for good secu­ri­ty prac­tices to be baked into busi­ness strate­gies.”

As long as dig­i­tal twins are deployed in a secure and safe way, the tech­nol­o­gy has the pow­er to trans­form man­u­fac­tur­ing qual­i­ty.