UPTIME FFT Use Case - Foresee Cluster

ForeSee is a cluster of six projects, which have received funding from the European Union’s Horizon 2020 research and innovation programme under the FoF-09-2017 call.

UPTIME FFT Use CasePredictive maintenance of complex mobile assets

Jeroen Versteeg, Senior Consultant, FFT Produktionssysteme

Predictive Project

Jeroen Versteeg – FFT Produktionssysteme

in a nutshell

11 Partners

3 Use cases

1 Unified Platform

DE

FR

I

E

I

TG

R

C

Y


UPTIME Vision

To reframe predictive maintenance strategy in a systematic and unified way by exploiting research advances in three main areas:

• Industry 4.0• I4.0 paves the way for extensive use of physical and virtual sensors generating a

multitude of data.

• Big Data Processing• Availability of big data leads to a strong demand for data-driven, real-time systems

incorporating efficient processing technologies in order to get meaningful insights about business performance.

• Proactive Computing• Proactive event-driven computing is referred to the use of event-driven systems for

mitigating future undesired events or for taking advantage of future opportunities.


FFT in a nutshell

Turnkey Body Shops

Turnkey Assembly Lines

Production Technology (Jigs & Tools)

Systems & Test Operations

Automation TechnologyMaintenance


FFT Use Case: Overview

• FFT is performing the maintenance under contract for a large european aircraft OEM's major aircraft components transportation jigs (in this case also built by FFT)

• Maintenance of these assets is crucial because they have to be highly available, air- and seaworthy, and are subjected to harsh environmental conditions

• There is a high coordination and reporting overhead in subcontracted maintenance projects


Main Challenges in the FFT Demonstrator Case

• High effort to ensure operational reliability:

• Airworthiness ensured by extensive Preflight Checks

• High effort for corrective and preventive maintenance

• Unknown asset condition results in inefficient preparation for maintenance activities

• High availability requirements

• Volatile and very short term notification for maintenance time slots

• No Spare Jigs available

• Difficult Identification of mishandling

• No feedback to FFT design team


Typical Failure Cases


Typical Failures

⚫ Structural failure

⚫ welding seam cracks

⚫ water/ice

⚫ Overloading (user error)

⚫ Collisions

⚫ Corrosion / aging

⚫ Lost parts

Typical Causes

⚫ Dynamic loading (vibrations, shaking)

⚫ Environmental stress

⚫ User error / user care


Status Quo of the Maintenance Project (2017)

• Planned Preventive Maintenance (PPM) and Corrective Maintenance only

• High dependency on customer production processes –high flexibility requirements

• High (manual) effort for asset identification, data collection and further processing (error prone Excel-based processes, manual work for KPI calculation)

• Often unknown condition and location of assets

• No Feedback of Maintenance Experience to the FFT Design Team

• In-Situ at Multiple Customer Sites



KPI and Enablers

Typical KPI

• On Time Delivery• Response Time

• MTTR Mean Time To Repair

• Asset availability

• On Quality Delivery• All Faults identified, documented and

corrected

• Identification of Root Causes

• Improvement Suggestions

• Operational reliability

• On Cost Delivery• 3% costs savings / year

• Flexible process planning and integration

• Any maintenance activity needs to be in-line with processes of the customer

• Maintenance activities driven by customer demands – planning difficult

• Continuous Information Management

• Transparent information availability to stakeholder

• Documentation of all activities

• Acquisition of asset condition

• Continuous Improvement

• Indicate weak processes and propose improvements

• Indicate weak areas(e.g. bottlenecks or sources of damages)

Enablers



Scope Definition - Requirements

1. Asset (Health) Data evaluation and management platform featuring:

• Data aggregation, post-processing and storage framework offering rule based automatic data

evaluation

• Capability to manage comprehensive maintenance process

• Transparent data access for different stakeholders

• Open interfaces (to enable integration to other (sub) platforms)

2. Physical asset data acquisition platform featuring:

• Capability to input and measure a wide range of physical quantities (implies development of reliable

methods to indirectly measure conditions by intelligent measurement)

• Modularity and Scalability: easy to add quantity (economic) and quality (additional physical quantities)

• Mobility (robust, unattended operation for extended periods, flexible means of data transmission)

• Certifiable for operation in-flight (Beluga transports)


Concept Vision

(Semi-mobile)

Hub

Mobile Sensor Module





Client Interface

•Operational Team

Client Interface

• Customer

Client Interface

•Design Team

Client Interface

• Planning Team

Evaluate•Rule based

condition assessment

Plan

Do•Perform

mainte-nance based on condition

Report / Document /

KPI

Optimise•optimise

evaluation rules

Aggregate

Private cloud

data storage

Maintenance Management

Platform


Hardware Development / Data Acquisition Platform

v1.5

v2.0

v2.5

SENSEnode

SENSEcore

v3.0


UPTIME Platform applied to FFT

UPTIME coverage of FFT-specific implementation focus:

UPTIME (Information) Platform

UPTIME_SENSEFFT Use Case /

Deployment


Data Acquisition

FFT SENSEnode Factsheet

❑ Size 65x30mm

❑ 2.4 GHz (BLE / WLAN)

❑ Sub-GHz (490-868 MHz) Long Range RF

✓ Range 1-2 km

❑ Sensors

✓ Motion and orientation

✓ Light

✓ Temperature

✓ Humidity

✓ Air pressure

✓ Force / Weight (Strain Gauges via ADCs)

❑ LEDs and LCD display

❑ Battery lifetime (AA cell) up to 1-2 years (sleep mode)


UPTIME - Stream Data Analytics

Presenter - Company

Exact location

during the

whole transport

cycle

Outlier forcast for

defined time span

Outlier gauges

Orientation:

compass

direction

Accelearation

e.g. shocks from

road bumps,

wholes, train

tracks, etc. and

outlier detection

Gyroscope:

orientation and

angular velocity

Asset selection


UPTIME - Batch Data Analytics

Presenter - Company

Filter selection and

combination Conducted Pre-Load

Checks and entries

per PLC

Gauges for quick

overview of figures

of main concern

Tags associated to

PLC entries based

on list of terms

Selection of fields from

Pre-Load Checks (PLC)

PLC entries according to

check routine conduction


UPTIME – Role Based Info Access

Stakeholder / Roles Example

“Fleet overview” with (per-asset) drill-down

functionalities generated from semi-structured

data (maintenance checklists).

Can be used by:

Maintenance Coordinator

⚫ trend analysis

⚫ priority identification

⚫ correlation finding

Engineer

⚫ hot spot identification

⚫ improvement effectivenes

Owner / Operator

⚫ Overview / trend analysis / reporting


ROI Projection (Example, “MaaS”)

Recall the main points of focus:

1) Maintenance Planning

2) Maintenance Execution

3) Reporting

4) (Continuous) Improvement

⚫ (Product + Process)

That was the return, so what about the investment?

Difficult to say (UPTIME doesn’t yet have a “price tag”), but let’s

consider effort for training and deployment, and assert that we

could be break even after approx. 1-1.5 years for projects with up

to ~15 p. permanent maintenance team.

(And better beyond that size!)

FFT’s Use Case “Special” Features:◆ “MaaS” (“Maintenance-as-a-Service”)

◆ Mobile and diverse assets, dynamic scope (“fleet” of assets)

◆ Additional layer(s) of “End User” type stakeholders


End User Assessment / Feedback

• Ergonomics/ease of use

⚫ Platform: intuitive web interface, puts useful asset data “at your fingertips”

⚫ Platform: the configurability/customisation within the platform (or a clearer indication which types of customisations are enabled and how) could still be improved. (Normal for the current state of the project).

⚫ SENSE: highly versatile product concept, supporting instumentation “on the fly”

• Utility

⚫ Enables on-demand health assessment of assets for multiple stakeholders

⚫ Delivers crucial planning input

⚫ Enables (continuous) improvement

• Impact for the end-user

⚫ Enables better focus on core tasks

⚫ Induces less waste (less need for “improvisation”)


Lessons learnt & next steps

• Lessons

⚫ Pilot deployment on assets not owned is challenging

⚫ Early integration is important

• Next Steps

⚫ Focus on partial deployments including focused improvements

⚫ Add UPTIME to “toolbox” for service projects

⚫ Add UPTIME to “toolbox” for optional inclusion in turn-key projects

• Relevance to European Manufacturing Industries

⚫ UPTIME has great potential to significantly lower the barrier to deploy a data driven integrated maintenance management platform (opinion)


Upcoming UPTIME Webinar

Live Webinar #3 10th December - “Lessons learnt and best practices in the Aviation industry” – FFT use case

Contact (FFT)

Jeroen Versteeg

FFT Produktionssysteme GmbH & Co. KG

Airbus-Allee 2,

28199 Bremen

[email protected]

UPTIME FFT Use Case - Foresee Cluster

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