1. Digital Paint Tools & Process Optimization NSRP All-Panel Meeting March 12, 2019
DCN#
Jamie Breakfield R&D Project Manager/Systems Engineer
Prepared under ONR Contract N D-0377 as part of the Navy ManTech Program

2. Project Team

3. What is the issue?
Need to improve the creation, handling and dissemination of paint data
Multiple disparate databases
Terminology across platforms not standard
Data format not standardized
Separate database for each hull
Difficult change management
Engineering and planning NEED to provide best possible data downstream
Painting in the shipyard is a major undertaking
Most every part of a ship will go through some degree of painting during construction.
Only certain areas in the shipyard are dedicated to performing major paint work and this limitation, coupled with the requirement to paint most parts, can often create a bottleneck to the rest of the construction processes taking place both before and after paint.
This problem is further exacerbated when paint has to be re-worked due to misapplication or error.
At the core of this issue is the ability of the upstream engineering and planning entities to provide the best possible data to the painters.
Currently the engineering and planning paint data is kept in a variety of places
multiple disparate databases
data format/terminology varies in each ship program
There is a major need and demand for a major change to the paint process and toolsets
The paint data needs to be standardized across all ship platforms, accessible as it changes, easy to maintain, and intuitive in its presentation.

4. Paint data quantified: What is a paint schedule?

5. Objectives Defined
Create a new optimized process for paint data management; Create a unified data tool to support
Streamlined process
Consolidate paint data
Standardize terminology & syntax across platforms
Increase efficiency
Reduce rework
Easily rate and plan paint execution
Manipulate paint data in conjunction with product model

6. What did we do? – Phase I
Conducted extensive assessment with stakeholders:
Discovery of all current paint data products and underlying process
Mapped current paint data process
Developed future process
Compiled detailed requirements set for functional development
Defined architecture based on functional requirements
Approved for public release (A); distribution unlimited

7. Map the Extent of the Current Process
What did we do? – Phase I
Identify all current paint-data driven products, producers, and consumers
Map the Extent of the Current Process

8. What did we do? – Phase I CURRENT !
Change process: Propagated manually per database
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover
Paint schedule and Deck
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover !
ERP ! !
Bills structured, estimated, created then bulk created in MARS via SQL, DWGs/aids manually attached individually
Unique MS Access
Databases - Per hull (Deck Covering & Paint)
Manual rollover, creation, or maintenance for each DB separately
Publish tabular products
(DBs replicated for billing)
Data calls, queries constructed as needed

9. Create New Process and Architecture
What did we do? – Phase I
Create New Process and Architecture

10. + + + PLM What did we do? – Phase I FUTURE ERP
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover
Paint schedule and Deck Paint schedule and Deck Cover
Paint schedule and Deck Cover +
ERP
Consolidated data set for all hulls & platforms
(Deck Covering & Paint)
Changes propagated automatically across centralized data set
Bills structured, estimated (more accurately), created, transacted to ERP in bulk with automated attachments
Automated rollover, efficient maintenance for all data together
Publish (release) live data with extraction capability
(no replication required) +
DESIGN MODEL
Increased utilization of design data (sq. ft., compartments, etc)
More Data Automation, Improved Data Quality and Less Manual Replication
Reduces time to perform billing and change paper activities
Reduces rework by improving data accuracy
Quickly serves the latest enhanced quality data to the work site +
Powerful queries easily built capable of searching all available data

11. Phase II - Approach Aras Innovator ShipConstructor
Develop the Digital Paint Tool as a single repository for all paint data
Interface with work provisioning system
Create a final document of the full paint schedule
Thousands of pages of paint coat, square footage, and location information
Creating a workflow to track paint changes with work provisioned
Alert to user when changes to the schedule have already been worked, or when changes can be sent
ShipConstructor
Extracting necessary information from ShipConstructor using Enterprise Hub PublisherLT Operations
Convert ShipConstructor data for automated square footage calculation
Geometry
Access
Provisioning
Legacy Data
Status
SSRS
Reports

12. Phase II - Results
Manage Paint Schedules and Locations

13. Phase II - Results
Add Paint Coats and General Notes

14. Phase II - Results
Manage Paint Work Orders

15. Initiate Notifications (real-time notifications for state changes)
Phase II - Results
Initiate Notifications (real-time notifications for state changes)
New
In Planning
In Review
Deleted

16. Phase II - Results
Robust reporting through SQL Reporting Services

17. Phase II – Key Points Aras Innovator provided an excellent foundation
Lifecycle, workflow, user management, data management, and /notification management are already included and easy to configure
Allowed the project team to focus on the more complex problems with paint
Aras provided an API that allowed us to sync large amounts of external data sources into the Aras system
Utilizing the ShipConstructor database structure to pull part information by unit
Calculate percentages of square footage for those rooms split by unit
Autocorrecting room boundaries that overlap
Syncing large datasets of provisioning data to be worked on a nightly basis

18. Conclusions/Next Steps
Consolidated digital paint process utilizes a single data management tool across all ship programs
Effectively uses the prior investments in the PLM platform to drive additional process improvements
Leverages digital thread/digital twin concepts to integrate the product model into the downstream planning and production processes
Similar concepts can be employed for other processes to drive additional value

19. Questions?