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1、WHITE PAPERGenerative AI(GenAI)in Aviation Maintenance,Repair,and Overhaul(MRO)April 2024By Nehal Reddy,Lacy Ketzner,Brian Hirshman,Chris Spafford and Neil McConachie1 GENERATIVE AI(GENAI)IN AVIATION MAINTENANCE,REPAIR,AND OVERHAUL(MRO)MRO providers play a critical role in ensuring the safety,airwor

2、thiness,and longevity of aircraft.They are essential to efficient and cost-effective operations for the aviation industry writ large.More is being asked of todays MRO providers-their already wide range of services will need to meet growing demand as the aviation industry continues to scale to meet r

3、elentless passenger demand(already nearing/exceeding pre-COVID levels).Doing more with less has been the necessity of the post 911 aviation space,but MRO providers need novel approaches to overcome current challenges of skilled labor shortages,prolonged supply chain constraints,and greater demand fo

4、r aircraft availability.Aerospace&Defense has typically been a late adopter of emerging technologies.The attitude can be described as“wait and see until this buzzword means something for us”because the cost-benefit of impacting your production process is not yet clear.Safety and compliance considera

5、tions also hinder speed to adoption,forcing thoughtful evaluation and consideration by nature.Once that hurdle is overcome,however,the industry is quick to respond.Machine learning,for example,is now standard practice using data to guide predictive maintenance to prevent operational maintenance rela

6、ted delays and more accurate materials forecasting,reducing materials/inventory spend.With all the attention that GenAI has received,MRO leaders may think more work is needed before it is ready to be adopted.This is not the case:GenAI is more than a buzzword.It is already a game-changer.In the follo

7、wing sections,we break down use cases that can help MRO providers improve efficiency across every stakeholder(back-office,engineering,and maintenance technicians)and where to start to accelerate your path to adopting this technology.BOSTON CONSULTING GROUP 2Exhibit 1Four Stages of Transformation:Imp

8、lementing GenAI in your MRO Organization1.Use Cases:How does GenAI help MRO providers?GenAI offers opportunities to improve processes across the spectrum.Basic administrative tasks like daily operational reports and metrics,regulatory reporting can be addressed through tools today,while transformati

9、onal capabilities require a strong data foundation few companies possess today.Below we detail different use cases MRO Providers and Operators should consider when identifying areas to improve with GenAI.Example Use CasesLevel of DifficultySupply Chain Risk analysis&prediction Inventory&price optimi

10、zation Supplier evaluationSales&Marketing RFP responses Marketing content generation Quote/pricing assistanceStage 1Sales&Back-OfficeSupport Functions Technician Guidance Asset lifecycle management“Owners manual”&procedure generationOperations Certification documentation support Logistics optimizati

11、on Maintenance schedule Conversational interfaceStage 3Front-line EnablementEngineering Generative design/copilot(incl.options)Suitable material identification Testing scenatio creationOperations(level II)Automated inspectation&repair guidance Root cause analysis Ad-hoc parts design/manufacturing to

12、 complete repairsStage 4Engineering&OPSLegal Contract gen.&review Document summaryAnalytics Data cleaning Metadata generationTraining&Knowledge Employee onboarding(inct.safety videos)Virtual recruiting Auto-generation of knowledge managementStage 2Legal,Analytics,Training3 GENERATIVE AI(GENAI)IN AVI

13、ATION MAINTENANCE,REPAIR,AND OVERHAUL(MRO)The line between Stage 1 and Stage 2 may look different across companies generally,moving from Stage 1 use cases towards Stage 2 implies an established data foundation that invites more risk-averse departments like Legal and Training,which can impact busines

14、s and service delivery,to adopt GenAI.Extending the technology to these use cases will not only save significant time to ensure contracting is not an obstacle to new business,but also begin upskilling their newer workforce.Specific examples use cases include:Proactive contract revisions based on rea

15、l-time business need instead of waiting for de-mand signals to make their way through multiple departments,GenAI can communciate the need for additional purchase orders or revised volume quantities.Empowering a newer workforce with reimagined trainings instead of depending on seasoned veterans to ta

16、ke on new apprentices,MRO Providers and Operators can offer a stronger base of materials to accelerate their learning curve,including step-by-step gener-ated repair procedures,troubleshooting tips and methods including video guided instruc-tions As GenAI continues to permeate functions,the need for

17、a streamlined approach to data capture,cleaning,and formatting to influence newer models becomes tablestakes.While initial forays may be more manual,companies will be unable to keep up without training GenAI to maintain data proactively.B.Stage 2 Legal,Analytics,and TrainingGenAI systems have improv

18、ed back-office functions for several years,using algorithms to optimize administrative tasks like inventory management and schedule administration.With its ability to handle a significantly larger set of constraints and dynamic inputs,GenAI outperforms existing back-office tools,helping Operators an

19、d Providers better optimize based on the new status quo with stressed supply chains,labor shortages,and over stressed networks.For organizations that consider themselves beginners,Sales&Back-Office functions are easier to begin with given existing approaches have likely already pushed companies to h

20、ave the data foundation(from quality and organization)that would yield promising results.Additionally,changes to processes in these functions are low-risk,making them ideal starter candidates for a high-regulation industry like A&D.With“plug-and-play”solutions across these use cases,organizations sh

21、ould be able to rapidly implement these tools into employees day-to-day and see quick wins in three broad forms:1 Efficiency savings by reducing manual tasks(e.g.,quarterly reports,PO generation,etc.)2 Multiplier savings by allowing employees to generate content(e.g.,RFP responses,contract reviews,t

22、raining material,baseline analytics code etc.)quicker3 Optimization savings by better tailoring inputs(inventory,supply chain,flex labor)to match needs through pattern recognition.A.Stage 1-Sales&Back-OfficeBOSTON CONSULTING GROUP 4GenAI offers the biggest productivity improvement to front-line work

23、ers since lean practices became standard in the 1970s.With greater demand for services and a significantly newer workforce due to COVID-induced retirements,MRO Operators and Providers need to accelerate their typical learning curve,effectively taking new trainees and having them perform like 20-year

24、 SMEs in a short timeframe.Such a feat requires not only imparting a large amount of knowledge on these newbies,but also molding their instincts to reduce time to diagnose and complete repairs.GenAI augments the front-line worker:through a combination of computer vision and documented repair protoco

25、ls,the tool can help a worker diagnose their specific job and walk he or she through step-by-step until it is completed.Before this type of attention would come at the expense of a veterans own productivity,whereas now,every worker has a personalized coach guiding them through repairs.And as compani

26、es have data indentifying better approaches via improved reliability,lower TAT from other workers,etc.,GenAI can automatically update procedures and repair techniques,vasting reducing time for reviews/approvals,discussions,etc.Stage 4 brings companies to the edge of GenAIs current capabilities.Where

27、as software engineers today can ideate,prototype,and review code with the assistance of GenAI,our ability to translate these skills from bits to atoms remains a challenge.The first obstacle is the fact that GenAI has yet to be developed around engineering principles,while the second requires compani

28、es to intelligently clean,format,and structure their data into a form ingestible by the training engine to then offer usable recommendations around design and testing.Some firms,like Autodesk,have begun building a GenAI layer atop of their existing 3D modeling software to begin to test these waters,

29、but we are still years away from being able to stretch this capability to more complex and tightly regulated structures like airplanes.Early results from enabling software engineers and product designers with GenAI give us a preview of the power of GenAI to aerospace and industrial engineers.When tr

30、ained on performance,maintenance,reliability,and other datasets engineers use daily to problem-solve,GenAI engines will be able to tackle the most labor-intensive activities for Operators MRO groups.Today,improving reliability requires engineers to analyze numerous data sets,bring together dozens of

31、 groups touching parts from different angles(procurement,front-line,engineering,etc.)to understand failure modes and identify addressable root causes.This step alone can take weeks given the amount of follow-up and additional analysis required.Once identified,engineers with different disciplines wil

32、l collaborate on corrective actions that address the root cause,while respecting constraints imposed by the FAA and cost targets.Instead,with a strong data foundation to support GenAI,much of the additional analysis can be done proactively by the analytics engine to identify probable root causes.Sim

33、ilarly,GenAI can proactively propose design recommendations that optimize on multiple constraints,e.g.,“the most sustainable option,”“speed to market”,or“cheapest to implement”.As such,Operators with these capabilities will be able to get more out of their fleet relative to a non-AI-assisted group.C

34、.Stage 3 Front-line EnablementD.Stage 4 Engineering&OPS5 GENERATIVE AI(GENAI)IN AVIATION MAINTENANCE,REPAIR,AND OVERHAUL(MRO)2.Where to StartWhere as many novel technologies become easier to implement as they mature along the hype curve,this is not the case for GenAI.The most important rule for work

35、ing with anything in AI is:“Garbage in.Garbage out.”Companies that fail to invest in their data strategy(from capture to format)will never have successful experiences with AI;if you mis-train the engine,it will fail to generate any usable output.Therefore,the first step towards implementing an AI is

36、 implementing a robust data strategy.Investing time now means more valuable data points to improve your future training models.Conversations at the C-Suite should help frame the goals,constraints,and timeline to drive progress and prioritization from the top down.As described above,quick wins by imp

37、lementing GenAI in proven use cases should help finance larger investments needed to graduate to Stages 3 and 4.At minimum,however,leadership should discuss:Financing foundational IT investments to support a best-in-class data strategy as the lega-cy tech stacks may not be fully equipped to do so Ad

38、ding data-minded talent(e.g.,data scientists,AI engineers,program managers with data experience):buying the tech is not enough,MROs must also invest in the human capital to tailor and sustain GenAI in the organization Guardrails and Risk Mitigations:AI suffers from three flaws Copyright infringement

39、,response bias,and hallucinations.Given the amount of regulation associated with MROs,leadership must design checks to minimize risk as it expands GenAI throughout various business unitsThis will be the most important technology investment that the industry makes in the foreseeable future.Without it

40、,MROs cannot overcome their labor and demand challenges.Any delay to starting now will only grow the obstacles to implementation down the line:those who fail to invest today may find it impossible to catch-up with GenAI-enabled competition within a few years.*In summary,service providers in the MRO

41、space should proactively adopt GenAI technologies.By embracing GenAI,MRO providers can significantly enhance their operations across various stages,from administrative efficiencies to frontline productivity and engineering innovations.The key to success lies in investing in a solid data foundation a

42、nd adopting a strategic approach to integrating GenAI into daily operations by prioritizing non-safety/non-compliance-sensitive use cases,MROs can effectively assess the technologys viability,leveraging early successes as stepping stones for further implementation.For further reading What is Generat

43、ive AI and How Does it Impact Businesses?|BCG hereBOSTON CONSULTING GROUP 6About the Authors:Nehal Reddy,Partner&Associate Director Nehal Reddy has 24 years of aviation experience with leadership roles in Maintenance Plan-ning,MRO marketing and product development and process engineering.I consulted

44、 with airlines on enterprise level systems integration programs,merger and acquisition transition planning,organizational change management,business process design and Lacy Ketzner is a Managing Director and Partner Lacy Ketzner is a core member of the Industrial Goods practice,leads the Aerospace a

45、nd Defense team at Boston Consulting Group in North America.She also leads the work in Digital for A&D globally,and is a core member of the Operations and Strategy practices.Lacy has deep expertise in supply chain,MRO(maintenance,repair,and operations),and program management in both the public and p

46、rivate sector.She has worked to drive business transformations and sustainable growth strategies.Ketzner.L Brian Hirshman,Managing Director and Senior Partner Brian Hirshman is heavily engaged in the Airlines and A&D practice areas.Brian is a seasoned aviation and aerospace professional that has con

47、sistently delivered tangible results over a 30+year career in airlines,professional services,and aviation maintenance,repair and overhaul(MRO).Hirshman.BChris Spafford,Managing Director&Partner Chris Spafford is a core member of the Industrial Goods and Consumer practices,and works with the worlds l

48、eading airlines,operators,OEMs(original equipment manufacturers),MROs(maintenance,repair,and overhaul),and financial sponsors in defining and executing their aftermarket strategies,enhancing their operations and cost positions,implementing digital solutions,and developing customer programs.Spafford.

49、C Neil McConachie,Managing Director&Partner Neil McConachie is part of the Airlines and Aerospace practice areas.Over the past 15 years,his work has focused on delivering large-scale cost transformation and digital modernization programs for airlines,MROs and OEMs around the world.He has extensive e

50、xperience with strategy development,cost take-out,crew productivity improvement,ERP system modernization as well as custom digital platform development to optimize cost and productivity across airline operations.McConachie.NBoston Consulting GroupBoston Consulting Group partners with leaders in busi

51、ness and society to tackle their most important challenges and capture their greatest opportunities.BCG was the pioneer in business strategy when it was founded in 1963.Today,we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholdersempowering organizati

52、ons to grow,build sustainable competitive advantage,and drive positive societal impact.Our diverse,global teams bring deep industry and functional expertise and a range of perspectives that question the status quo and spark change.BCG delivers solutions through leading-edge management consulting,tec

53、hnology and design,and corporate and digital ventures.We work in a uniquely collaborative model across the firm and throughout all levels of the client organization,fueled by the goal of helping our clients thrive and enabling them to make the world a better place.Boston Consulting Group 2024.All rights reserved.03/24 For information or permission to reprint,please contact BCG at .To find the latest BCG content and register to receive e-alerts on this topic or others,please visit .Follow Boston Consulting Group on Facebook and T