Data-Driven Reconfigurable Manufacturing Systems For The Air Force Aircraft Maintenance Environment JTEG Technology Forum: Facility Maintenance 31 July 2018 Aging Aircraft Consulting James Hill, Principal Investigator james.hill@aacl.aero 478-225-4044 402 AMXG/WR-ALC/AFSC Joshua Campbell, Deputy Director 572 AMXS Joshua.campbell.12@us.af.mil SBIR DATA RIGHTS Contract No. FA8501-17-C-0025 Aging Aircraft Consulting LLC, 64 Green Street, Warner Robins, GA 31093 Expiration of SBIR Data Rights Period: 14 Oct 2024 The Government's rights to use, modify, reproduce, release, perform, display, or disclose technical data or computer software marked with this legend are restricted during the period shown as provided in paragraph (b)(4) of the Rights in Noncommercial Technical Data and Computer Software--Small Business Innovative Research (SBIR) Program clause contained in the above identified contract. No restrictions apply after the expiration date shown above. Any reproduction of technical data, computer software, or portions thereof marked with this legend must also reproduce the markings.

Aging Aircraft Consulting | Subject to SBIR Data Rights Goal Develop & deliver a model to adapt Reconfigurable Manufacturing Systems (RMS) to the maintenance environment at the Air Force ALCs, specifically WR-ALC Increase manufacturing agility to product changes Change capacity to meet demand Responsive to changing conditions Objectives SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Deliverables: Strategic RMS Simulation Model for Warner Robins ALC to assist 558 AMXS planning for de-paint and paint processes and facilities over a 5 year period Simulation scenario results Virtual model “digital twin” of paint hanger and associated equipment Aging Aircraft Consulting | Subject to SBIR Data Rights

Reconfigurable Manufacturing Systems Overview Tight integration of depot manufacturing processes make them hard to modify to changing requirements, demand and product changes Reconfigurable Manufacturing Systems Overview Projection compared to actual product demand: higher initial demand than expected for both products, and product C is introduced earlier than expected. Three features – capacity, functionality, and cost – are what differentiate the three types of manufacturing systems — RMS, DML and FMS. While DML and FMS are usually fixed at the capacity-functionality plane, as shown in Fig. 2, RMS are not constrained by capacity or by functionality, and are capable of changing over time in response to changing market circumstances. Adapted from: *Yoram Koren, Moshe Shpitalni, Design of reconfigurable manufacturing systems, Journal of Manufacturing Systems, 29 (2010), pp. 130– 141 DML = Dedicated Manufacturing Line FMS = Flexible Manufacturing Systems RMS = Reconfigurable Manufacturing Systems Manufacturing system cost versus capacity. Aging Aircraft Consulting | Subject to SBIR Data Rights

Questions this Technology can Answer When will be the best time to schedule maintenance for these facilities to optimize maintenance workflow? How can I build a business case for making a facility reconfigurable for current or future processes or uses? How can I plan for new facilities to be capable of handing workload or products that have not yet been identified? How can I build a business case to build reconfigurable features into a new facility? What benefit can robotics integrated into a facility have on maintenance processes or facility utilization? How can I use a ”digital twin” of a facility to optimize maintenance processes and facility layouts? Questions this Technology can Answer Aging Aircraft Consulting | Subject to SBIR Data Rights

Aging Aircraft Consulting | Subject to SBIR Data Rights WR-ALC 558 AMXS Corrosion Control Flight (CCF) Facilities CCF at Robins AFB Building 59P SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Building 59D Building 50 (C-130 de-paint) Building 54 (C-17/C-5 de-paint) Building 89 (C-130 paint) Aging Aircraft Consulting | Subject to SBIR Data Rights

Phase II Technical Objectives 1 2 3 Create high-fidelity simulation tool for RMS evaluation Create a simulation optimization function Build a Digital Twin of a facility to perform virtual reconfigurable layout analysis Phase II Technical Objectives SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Roadmap Understanding current practices & data collection Develop high fidelity simulation model Scenario Analysis, Validation of the scenarios through engineering knowledge Simulation based optimization Virtual RMS study Delivery and training SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Technical Approach Summary Data Driven Methods Historical Data PDM Process Analysis Available Resources Engineering Knowledge Technical Approach Summary SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Adapted to Air Force Environment & Processes RMS Model Aging Aircraft Consulting | Subject to SBIR Data Rights

RMS Model Development Process Gathering the engineering knowledge: Processes Available resources Shared resources In-house or outsourced operations Required machines Facility utilizations Historical data RMS Model Development Process Input Analysis Test the independence of the collected data and to estimate appropriate distributions that fit the data accurately. Fit parametric or empirical distributions to the data Simulation model validation Build simulation model Validate model business rules Back test model output SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Scenario analysis Define Simulation Scenarios Evaluate Performance of Simulated Scenarios Output Analysis Aging Aircraft Consulting | Subject to SBIR Data Rights

Model development & validation SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Data Collection & Validation Process Problem: Raw historical process data can be scattered across multiple data systems and is usually not in a format to allow analysis and statistical analysis. Therefore a focused process needs to be used to collect and process data to achieve defined requirements. Determine objectives & requirements What are we trying to predict and for what goal? In what form do we need the output? Identify data required to achieve objectives What data do we need to make the prediction? Locate & evaluate existing data Where is that data located? In what format is the data? Clean and transform data Document business rules to transform data for analysis Develop automated tools to transform data Perform input analysis & analytics Analyze and validate data using engineering knowledge Data is now in a usable form! Data Collection & Validation Process SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Simulation based optimization SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting The goal of the simulation-based optimization is to find best set of controllable values that optimizes the system performance minimizing cost minimizing the maintenance delay and cycle maximizing facility utilization The active learning module performs as a filter to identify the most influential points to optimize the simulation Aging Aircraft Consulting | Subject to SBIR Data Rights

Virtual RMS Implementation Create a Digital Twin of one Paint or De-Paint Facility to optimize configuration and evaluate 3D simulation processes, Laser scan facility 3D Model area Virtual layout Fly throughs Perform plant layout analysis to reduce reconfigurable switching costs and improve overall efficiency SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Phase II Technical Objectives High-fidelity simulation tool for RMS evaluation Phase II Technical Objectives Digital Twin – Virtual reconfigurable layout analysis Simulation optimization function SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting New Capabilities Strategic: Quickly run reconfigurable scenario analysis over multiple years to assess operational impact and overall throughput Tactical: use digital twin to evaluate reconfigurable improvements & optimization Aging Aircraft Consulting | Subject to SBIR Data Rights

558th AMXS Operational Objectives Throughput Capacity Utilization SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Desired Operational Outcomes Increase capacity over multiple years Take on increased workload volume Take on new product workload Aging Aircraft Consulting | Subject to SBIR Data Rights

Vision for RMS Data Driven Model A decision support tool connecting material & resource needs of AMXG, and the ALC enterprise the ability to assess tradeoffs between maintenance groups to optimize overall cost, schedule and throughput. Vision for RMS Data Driven Model For AMXG Ability to reconfigure resources based on changes in demand and process optimization results Quickly perform long term planning analysis and scenarios to enable reconfigurable benefits analysis Tactical model for day to day decision support For WR-ALC (enterprise view) Ability to assess the cost tradeoffs between AMXG and CMXG workloads to optimize overall maintenance cost, schedule and throughput SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Predictions & Decision Making Prediction is the process of filling in missing information. Prediction takes information you have (“data”), and uses it to generate information you don’t have. The RMS model is a decision support tool that lowers the cost and time required to make predictions about the future state of the manufacturing machine. The drop in cost of prediction increases the value of complements Data Judgement Action More accurate predictions can help increase the quality of decisions. Results of decisions can be measured and fed back into the model to increase the accuracy of future predictions Predictions & Decision Making SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights

Aging Aircraft Consulting | Subject to SBIR Data Rights Thank you! Input and feedback is welcome Aging Aircraft Consulting James Hill – 478-225-4044 james.hill@aacl.aero Discussion SBIR Topic: AF161-019 Data-Driven Reconfigurable Manufacturing Systems for the AF Maintenance Environment Aging Aircraft Consulting Aging Aircraft Consulting | Subject to SBIR Data Rights