UK perspective on Digital Manufacturing...PLATFORM FORPROCESS-AND SERVICE-INTEGRATION • End2End combination of connected devices between users, care services, family members and

UK perspective on Digital ManufacturingLord Prior of Brampton,

former Parliamentary Under Secretary of State

TOPIC ONE: IMPLEMENTATION

Lars Nagel, Managing Director, Industrial Data Space Association

Chris Biddle, Global Business Development Manager, ATS Global

Christian Warden, Head of Skills Development, MTC Advanced Manufacturing Training Centre

Moderator: Dr Steven Barr, Managing Director, Hennik Edge

Cyber security and data sovereignty Lars Nagel, Managing Director, Industrial Data Space Association

A NEW IDEA FOR SHARING DATAINDUSTRIAL DATA SPACE

Digtalising Manufacturing Conference 2017 @ mtc, Coventry, 31.10.2017Lars Nagel, Managing Director

InteroperabilityData Exchange

»Sharing Economy«Data Centric Services

Data OwnershipData SecurityData Value

WE HAVE A NEW IDEAFOR SHARING DATA

is the ability of a natural orlegal person to exclusivelyand sovereignly decideconcerning the usage of dataas an economic asset.

DIGITAL SOVEREIGNTY

SENSOR DATAMATERIAL CHARACTERISTICSMOBILITY DATAFINANCIAL DATATECHNICAL DRAWINGS

OBSTACLES CONCERNINGEXTENSIVE SHARING OF DATA

© y on PwC-Stud "Industrial Data Space"

57%worry about revealingvaluable data andbusiness secrets.

59%fear the loss ofcontrol over theirdata.

55%feel inconsistentprocesses andsystems as a (very) big obstacle.

32%fear that platforms do not reach the criticalmass, so that dataexchange will beinteresting.

Optimising Processesand Cost Structures

Improvement ofSovereignty

More Data Security Join us!

Today

IndustrialData SpaceApproach

INDUSTRIAL DATA SPACE –THIS IS OUR MISSION:

MISSION STATEMENT

The INDUSTRIAL DATASPACE ASSOCIATION defines the basic conditions and governance for a reference architecture and interfaces with the objective of setting up an international standard.

INTERNATIONAL STANDARDS

This standard isactively developedand updated onthe basis of usecases.

USE CASES

INDUSTRIAL DATA SPACEstands for secure data exchange between companies in which the data provider is always the owner of that data and still keeps control over the use of their data.

SECURE DATA EXCHANGE

It forms the basis for a variety of certifiable software solutions, smart services and business models, the development of which is encouraged by the association.

BUSINESS MODELS

1

2

4 3

www.industrialdataspace.org // 10

80+Companies and

Organisations

5Working Groups

20+Use

Cases

1Ecosystem

=

http://logenios.com/de

http://logenios.com/de

https://www.google.de/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwjt2tv5lJTSAhXKaRQKHSUVDVEQjRwIBw&url=https://www.chalmers.se/en/about-chalmers/profile-and-identity/Pages/logotype.aspx&psig=AFQjCNF8GiN6IprO-jNtzAyYK-khm9eNLA&ust=1487318860726896


https://www.google.de/imgres?imgurl=http://hoko-online.de/images/content/2016/firmenlogos/02_donnerstag/logo-msgsystems.jpg&imgrefurl=http://hoko-online.de/studenten/firmenuebersicht/donnerstag.html&docid=gcs_7SRNGtiBsM&tbnid=L1ll85-UdNSg6M:&vet=1&w=11811&h=3677&bih=719&biw=1536&q=Logo%20msg%20systems&ved=0ahUKEwirzaa4l5TSAhVHOBQKHUJhDFQQMwhHKB8wHw&iact=mrc&uact=8

https://www.google.de/imgres?imgurl=http://hoko-online.de/images/content/2016/firmenlogos/02_donnerstag/logo-msgsystems.jpg&imgrefurl=http://hoko-online.de/studenten/firmenuebersicht/donnerstag.html&docid=gcs_7SRNGtiBsM&tbnid=L1ll85-UdNSg6M:&vet=1&w=11811&h=3677&bih=719&biw=1536&q=Logo%20msg%20systems&ved=0ahUKEwirzaa4l5TSAhVHOBQKHUJhDFQQMwhHKB8wHw&iact=mrc&uact=8

https://www.vdma.org/

https://www.vdma.org/

http://www.polimi.it/index.php?L=1

http://www.polimi.it/index.php?L=1


ARCHITECTURE FOR DATA AND DATA SERVICESAN INFRASTRUCTURE FOR ALL INDUSTRIES AND DOMAINS

Automotive Electronicsand IT Logistics Retail and Food Health

… (other Industries)

Smart-Service-Scenarios

Service and product innovations

»Smart Data Services« (alerting, monitoring, data quality etc.)

»Basic Data Services« (information fusion, mapping, aggregation etc.)

Internet of Things ∙ broad band infrastructure ∙ 5G

Real Time Area ∙ sensors, actuators, devices

Arc

hite

ctur

ele

vel

INDUSTRIAL DATA SPACE


ARCHITECTURE FOR DATA AND DATA SERVICESAN INFRASTRUCTURE FOR ALL INDUSTRIES AND DOMAINS

Automotive Electronicsand IT Logistics Retail and Food Health

… (other Industries)

Smart-Service-Scenarios

Service and product innovations

»Smart Data Services« (alerting, monitoring, data quality etc.)

»Basic Data Services« (information fusion, mapping, aggregation etc.)

Internet of Things ∙ broad band infrastructure ∙ 5G

Real Time Area ∙ sensors, actuators, devices

Arc

hite

ctur

ele

vel

INDUSTRIAL DATA SPACE


A PEER TO PEER APPROACHTO STANDARDISEDLY CONNECT PLATFORMS AND THINGS

PLANNING, EXECUTION, CONTROL(MULTI-SIDED PLATFORMS)

Traffic Weather

OPEN CONTEXT DATA

Actors Sensors Machines

IoT Clouds

Domain specific platforms

Marketplaces

BrokerConsumerProduction

FIELD VIEW(FACTORY)

VALUE CHAIN

It‘s all about sharing data!

www.industrialdataspace.org

OK.

// 14

What‘s new?

www.industrialdataspace.org

OK.WHAT‘S NEW?

// 15

Self determined control of data flows in a peer to peer approach:

Endless Connectivity –standard for data flows

between all kinds ofdata endpoints

Comprehensivesecurity functions

providing a maximumlevel of trust

Usage control andenforcement for data

flows


VALUE PROPOSITIONINDUSTRIAL DATA SPACE CONTRIBUTES THIS:

Everything needs to be secure• Authentification & Authorisation • Usage Policies & Usage Enforcement• Trustworthy Communication• Security by Design • Techn. Certification

SECURITY

Connection of every data endpoint• Integration of existing vocabularies• Using different data formats• Connection of clouds and platforms

STANDARDIZEDCONNECTIVITY Data is being traded as an asset

• Clearing & Billing• Domain specific Broker and

Marketplaces• Legal Aspects (Contract

Templates, etc.)

DATA MARKETS

Being able to explain, find and understand data• Data source description• Brokering• Vocabulary

ECOSYSTEM OF DATA

Typical tasks can be solved easier with apps• Processing of Data• Remote Execution

VALUE ADDING APPS

Trust is the basis of the IDS• Identitymanagement• User-certification

TRUST1 2 3

4 5 6


REFERENCE ARCHITECTURE MODELINTERACTIONS OF COMPONENTS ON THE SYSTEM LAYER

Industrial Data Space

Information

System

Process

Functional

Business

Secu

rity

Cert

ifica

tion

Gove

rnan

ce

Layers Perspectives

BrokerAppStore

Data Source

Connector

Data Provider Data Consumer

Dataset(s) transferred from Provider to Consumer

Metadata Description ofDatasets/Provider/Consumer

Application for specific datamanipulation

Data exchange (active)

App download

Metadata exchange

Data exchange (inactive)

Connector Data Sink

Connector

MetaMeta

MetaMeta

Meta

Peer-to-peer nodes

App

Data

Meta

AppApp

App

App

Data

Meta


DISTRIBUTED GOVERNANCE IN THE INDUSTRIAL DATA SPACE ECOSYSTEM

Runtime EnvironmentRuntime Environment

authorize

publish app

transfer data

data flow

metadata flow

software flowidentification

use

IDS

soft

war

e

use

IDS

soft

war

e

use

IDS

soft

war

e

identify

Data Owner

AppProvider

VocabularyProvider

Clearing House

App StoreProvider

IdentityProvider

DataConsumer

Broker Service

Provider

Service Provider

Software Provider

Data Provider

Certification mandatory

Membership in the IDSA mandatory

Depends on service provided

optional

Certification Authority

Depends on service provided


Operating System

Virtual Machine / Hardware

Validator

Configurator Management

NetworkExecution

Configurator

WorkflowExecution

Configurator

Application Container Management

Runtime Runtime Runtime

APIAPI MessageRouter

MessageBus

Execution Configuration

Custom Container

App Store Container

ExecutionCore Container

ConfigurationManager

Data Service Data Service Execution Core

Configuration model

…

Runtime

REFERENCE ARCHITECTURE MODELREFERENCE ARCHITECTURE OF THE CONNECTOR

Connector Types

Base Trusted

Internal External

Developer, Mobile,Embedded, Custom, …

Industrial Data Space

Information

System

Process

Functional

Business

Secu

rity

Cert

ifica

tion

Gove

rnan

ce

Layers Perspectives


TRUSTED CONNECTOR Focus

• Connectors withdifferent securityprofiles from basefunctionalities to highestsecurity requirements

• i. e. remote integrityverfication, secure dataerasure, TPM 2.0, remote app execution, mutual authentification, …


• Connectors communicatewith each other throughan IDS protocol (IDSP)

− Secure Websocketsover TLS

− Remote Attestation & Meta Data Exchange: Proof of trustedplatform configuration

• Exchange of payload datawith an associated usagepolicy

• Connection of backend protocols through protocoladapters. 200+ supportedprotocols (REST, MQTT, OPC-UA, AMPQ, …)

COMMUNICATION Focus

Smart Sensor

IDS Connector Producer

Core Container

Container Managemement Layer

TPMd

Custom Container 1

OPC-UA ClientSystem Adapter

Attestation Manager

Custom Container 2

ExternalData Service

Container Manager

IDS Connector ConsumerCore Container

Container Managemement Layer

TPMd

Camel

Custom Container 1

Data Service

IDS Protocol

Custom Container 3

Data Filtering

Sensor Application

OPC-UA Server

TPMd

Data Signing

System / HW Interfaces

System / HW Interfaces

Policy Manager

CamelPEP

IDS Protocol EndpointPEP

IDS Protocol Endpoint

Admin GUI Admin GUI

Route Manager

Configuration Manager

Camel IDS Protocol Endpoint

Attestation Manager

Policy Manager

Route Manager

Container Manager

Configuration Manager

Message Processor

Message Processor

Custom Container 4

Production Feedback

Trusted connector scenario


• Usage policies can beattached to data sourcesor data items

• Policies are signed by thesource connector and canbe verified by the targetconnector

• The policy set can be seenas a usage contract

• Different solutions: labelbased usage contrrol, distributed usage control, sticky policies, remote processing

USAGE CONTROL - POLICIES

Custom Container Core Container

Data Service Message Queue

Data Flow Control

Connection Mgmt.

Trusted Container Management Layer

Core Container

Message Queue

Data Flow Control

Connection Mgmt.

Trusted Container Management Layer

Custom Container

Target App

IDS Protocol

personal AND raw require(logging), delete_after(30 days)

Labels Constraints

Focus


• Policies for sticking tousage restrictions –concerning the dataproducer (compliance, legal regulations) and thedata consumer(obligations from the dataproducer)

USAGE CONTROL - POLICIES Focus

A B

• Data with thelabel „personal“ may only beforwardedinternally

• Data may not leavethe european legal area

• Data with the label„personal“ must beanonymised

• Data producer tobe informed at each usage of dataset

• Data may beused max. 5 times and must be deleted after 14 days

• Deletion will belogged


• Example from theautomotive industry

• Sharing data between tier-1 supplier and OEM

• Usage control andexecution mechanism

MANAGEMENT OF DISTRIBUTED USAGE CONTROL Focus


OUR USE CASES MAKE IT HAPPENINDUSTRIAL DATA SPACE IN ACTION

The use cases demonstrate the innovations based on Industrial Data Space

Potential core of an ecosystem by integrating further partners (also from different domains)

Each member of the associationrealizes a business driven use case

CHARACTERISTICS OF IDEAL USE CASES:

• Link data from several data sources• Integrate various kinds of data

(for example master data and status data in manufacturing)

• Combine various data goods(private and public data, »club goods«)

• Involve at least two companies• Integrate more than two company architecture levels

(for example »shop floor« and »office floor«)• Basis for offering »smart services« • Develop core components/basic services

!

!

++

+


Short Description• Phase 1: Event based transfer

of effected Supply Chain data

• Phase 2:Event based transfer of material flow data

COLLABORATIVE SUPPLY CHAIN RISK MANAGEMENT

Benefits

+ On demand Supply Chain Transparency + Realtime Tracking and Tracing+ Proactive Supply Chain Risk Management

OUR USE CASES MAKE IT HAPPEN

Main Technology/IDS Components• Internal and external IDS

connector• Vocabulary• Bosch Tracking & Tracing

Partners/Ecosystem• Logistics Service Provider

(tbd.)• Tier-2 Supplier (tbd.)

Targets• Set of rules• Standardized data definitions• Harmonized data model• Proof of concept for the data

transfer


• Time Slot Management, Dynamic Estimated Time of Arrvial and Track & Trace

• Integrating all existing telematics systems

• Ensuring maximum connectivity to all logistics service providers

• Using GS1 EDI XML as common message standard

• Comprehensive status changes

DIGITAL LINKING OF A PRODUCTION LINE

• Semantic standards for the Machine 4.0 (RDF)

• Combining of production, replenishment, maintainence, quality management

• Exchanging data along the whole production line and supply chain

• Combining vocabularies• Reference technology stack

for a machine 4.0

DYNAMIC TIMESLOT MANAGEMENT AND TRACKING IN THE SUPPLY CHAIN

+ Automatic matching of tool and order data+ Minimizing tooling time+ Correlation of machine and work piece

Benefits Benefits

+ Reducing traffic jams and out of stock situations+ Time slot management in realtime+ Better data quality for planning



• Merging of procurement systems

• Automatic management of semantic description of steel quality criterias

• Machine interface for availability

• Transparency and fast response time to customers

BROKER BASED DESIGN OF SUPPLY CHAINS

• Small lot sizes make adhocactions necessary

• Orchestration of all network partners (Logistic service providers) to fulfill orders

• Selforganised configuration of a transportation order

• Tender management

INTELLIGENT STOCK INFORMATION

+ Tailormade supply chains on demand+ More transparency and options

+ Reducing the connections to suppliers+ Procurement in realtime+ Better quality by reducing misinformation

Benefits Benefits




SMART CARE PLATFORM FOR PROCESS- AND SERVICE-INTEGRATION

• End2End combination of connected devices between users, care services, family members and medical institutions

• Harmonization of various data protocols, transmission media, across vendors, users and institutions.

• Pre-requisite for implementing multi-local smart care services, e.g. in rural regions

+ Overcome babylonic variety of proprietary protocols

+ Elimination of barriers to mass-roll-out of smart care solutions

+ Data sovereignityBenefits

Health Industry

Facility Mgt.

Corporate Health

Mgt

Care Industry

Smart Cities

Insurance Sector

Smart Care Platform

PLATFORM INTEGRATION OF EQUIPMENT VIA OPC UA

• Integration of equipment via industrial standards like OPA UA

• Modular service based concept allows extension for semantic technologies or other protocols

• Support for horizontal integration across value chains

• Linking with platform and cloud services

+ OPC UA standard protocol integration+ Platform connectivity via IDS secure channel

Benefits

OPC UA Connector


MILESTONES REACHEDAND NEXT STEPS

ARCHITECTURE

Release of thereference architecture

model 2.0 on Hannover Fair

INTERNATIONAL

Members all over theworld, connecting withimportant initiatives,

major european RTOs, intense engagement in

european researchactivities

STANDARD

Foundation of a workinggroup at DIN to

create a DIN specificationfor the IDS connector

GO LIVE

Ecosystem potentiallyrunning, first products,

enhancing global adoption


LIAISONS AND STRATEGIC ALLIANCESOVERVIEW

Initiatives

Institutions Projects

Research Partners

CBA Labs

OpenAAS

Smart Factory KLVirtual Fort Knox

Fitman

I4MS



www.industrialdataspace.org // 32Spreading our idea globally

mtc is our partner in UK

Common targets:• Bringing more adopters of IDS to our ecosystem and create

a vital subcommunity• Setting up new use cases• Delivering new requirements• Knowledge transfer• Bringing IDS to national research calls• Placing IDS on the EU roadmap• Supporting international positioning

SPREADING IDS GLOBALLYCENTRAL HUBS EMPHASIZE ADOPTION


Become a member

StartYOUR WAY THROUGH THEINDUSTRIAL DATA SPACE ASSOCIATION

1ACQUIRE BASICKNOWLEDGE ON INDUSTRIAL DATA SPACE

Just start reading and gainingknowledge on Industrial Data Space and the Association(whitepaper, presentations)

Important Documents to be known:

Reference Architecture

Use Case Overview

Sprint Releases Reference Use cases anddocumentation(image file + source code + docker container)

PwC Study on Data Sharing (German)

http://www.industrialdataspace.org/download/

2Send people toworking groups

START CO-CREATINGTHE INDUSTRIAL DATA SPACE

Engage on JIVE

https://industrialdataspace.jiveon.com(apply for access via website or head office – members only)

Login via:

Access credentials on JIVE:

Try out reference use cases – test IDS on your devices:

• working group architecture• working group use cases & requirements• working group certification• taskforce exploitation and business modeling• taskforce legal framework

http://www.industrialdataspace.org/download/


3

Find your role in the Industrial Data Space ecosystem and build

services or products

SET UP YOUR OWNUSE CASE

4ROLL-OUT INDUSTRIAL DATA SPACE IN MORETHAN ONE SCENARIO

Use case process – if you are stuck, contact the head office. We guide youthrough the use case process.

Market conquest

5MAKE YOUR OWNINDUSTRIAL DATA SPACE BUSINESSCASE

Describe andcommunicate your

use case

Bring your use case on the IDSA use case map

Pitch your use case in the wg use cases & requirements

Get inspiration fromothers use cases

Add your requirements to the functional overview, so that it can be considerated in future architecture and sprint

release and helps improving the Industrial Data Space:

https://idsspec.isst.fraunhofer.de/idsspec

// 35

JOIN US !LARS NAGEL

MANAGING DIRECTORINDUSTRIAL DATA SPACE ASSOCIATION

WWW.LINKEDIN.COM/IN/LARS-NAGEL-704411B8/

JOSEPH-VON-FRAUNHOFER-STR. 2-444227 DORTMUND | GERMANY

+49 231 9743 [email protected]

@ids_association#industrialdataspace

www.industrialdataspace.orgRessource Hub – Press Area – Blog

Connectivity and interoperability: Implementation of machine tool connectivity in global aerospace manufacturing. A case study based upon experiences at Rolls-Royce.Chris Biddle,

Global Business Development Manager, ATS Global

www.ats-global.comThe Independent Solution Provider

37

Implementation of Machine Tool Connectivity in Global Aerospace Manufacturing

Christopher BiddleGlobal Strategic Business

Development Director


38

Digitalisation and Industry 4.0


39

Connection Deployment of infrastructure, cabling, IoT sensors, and shop floor IT

What is Industry 4.0?

Acquisition Collecting Key Process Variable, Inspection and Operational Data

Contextualisation Tagging and transmitting data to give it meaning

Aggregation Associating related pieces of meaningful data together to form information

Visualisation Interrogating the associated data to bring insight into what has happened

Prediction Using trends, algorithms and statistical analyses to determine what is likely to happen next

Prescription Setting up rules as standard responses to predicted outcomes

Cognition System uses its own experience to plan for and respond to predicted outcomes – applied knowledge

Incr

easi

ng V

alue

His

tory

and

Exp

erie

nce

Inte

rven

tion

UnderlyingTechnologies

0100101001010


40

First Generation Connectivity

• Individual, segregated plant floor networks

• Machine by machine configuration• Separate software for each type of

data Introduced Management of Shop Floor

IT Devices for the first time Overcame perceived robustness and

security issues Very costly to implement and maintain

with limited data visibility

Enterprise Network

Shop Floor

Network

Connection, Acquisition and Contextualisation

Point Solution Model

http://h10010.www1.hp.com/wwpc/uk/en/ho/WF02a/35123-35527-187917.html



41

Second Generation Connectivity

Plant MES Plant Middleware

OEM Software Interface

Enterprise Network

Shop Floor Network

• Individual, virtualised plant floor networks• Machine by machine solutions Good delivery of high performance

functionality for low-volume, single piece flow

Individual testing of each solution Poor or zero skills in OEM to develop the

required interfaces – limited understanding of Functional Design Specification

Changing functionality in the MES caused multiple changes in OEM interface

Connection, Acquisition, Contextualisation, Aggregation and

Visualisation

Translator/Broker Model




42

Third Generation Connectivity

Enterprise MES

Plant Middleware

Data Collector

Enterprise Network

Shop Floor Network

• Standardised solutionOEM Independent Changing functionality in the MES

causes relatively few changes in the middleware

Introduces latency, decreasing performance – originally designed for batch, now used as single piece

High Burden of Configuration/Data Dictionary Management

Stretches the capability of underlying SCADA software

Data Collector In A Box ModelConnection, Acquisition,

Contextualisation, Aggregation, Visualisation and Prescription




43

Evolution of Capability

Connection

Acquisition

Contextualisation

Aggregation

Visualisation

Prediction

Prescription

Cognition

Incr

easi

ng V

alue

FirstGeneration

SecondGeneration

ThirdGeneration

Dec

reas

ing

Cos

t, bu

t als

oD

ecre

asin

g Pe

rfor

man

ce

Business continuity of individual manufacturing cell, production line and work center

Machine to machine, part to machine and tool and fixture to machine collaboration

Enterprise and Manufacturing IT systems to machines communication

Communication among all OT/IT heterogeneous systems

Industry 4.0 Requires:


44

“Industry 4.0” Implementation

Business continuity of individual manufacturing cell, production line and work center

Machine to machine, part to machine and tool and fixture to machine collaboration

Enterprise and Manufacturing IT systems to machines communication

Communication among all OT/IT heterogeneous systems

Industry 4.0 Requires:


45

Case Study 1:

Strategic Goals

• Productivity increase while lowering operative costs

• Flexible production – batch size one

• Rapid ramp-up and downscale of production systems

• Autonomous responsiveness to disruptive events and demand fluctuations

Automated Aerospace Assembly


46

Case Study 2:

Strategic Goals

• Increase Operational Efficiency• Reduce 80% defects in final

product using real-time analytics• Location awareness of the board

and full traceability of consumables and products

• Improve lead-time through flexible routing

Electronic Manufacturing Line


ATS, The Independent Solution ProviderTHANK YOU!

Smart Automation, Qualityand IT Excellence SolutionsTHANK YOU!

Smart Automation, Qualityand IT Excellence SolutionsTHANK [email protected]

Skills and training – a digital competence frameworkChristian Warden,

Head of Skills Development, MTC Advanced Manufacturing Training Centre

Implementing Digital SkillsCreating Competence

Christian Warden

The changing landscape of manufacturing skillsEmbracing the fourth industrial revolution

2017

The changing landscape of manufacturing skillsEmbracing the fourth industrial revolution

2020+

Competitive Capability is essential!Are we ready to compete in an increasingly digitised world?

Digital skills in manufacturing, what does it mean? Automation and Robotics Additive Manufacturing (3D Printing) Advanced Manufacturing processes Human-machine interaction Artificial Intelligence

The AMTC: Advanced Engineering Apprenticeships Upskilling, Re-skilling, Multi skilling existing employees Employer led, employer integration, future focused

The AMTC leading the evolution Embracing and implementing Digital skills

Source:KPMG

The AMTC Apprenticeships, Training and DevelopmentBusiness impact and genuine progression from Level 2 to Level 7

The AMTC Advanced Manufacturing Skills Solution

A forward facing programme, providing a pipeline of future proof talent

Apprentices receive knowledge and skills

in emerging technologies, including digital

skills and Industry 4.0

Learning takes place in and around many

advanced projects with technology applied

All apprentices essentially ‘over-trained’ when

compared to current standards

MTC programme highly attractive

MTC create a pipeline of future-proof talent

with known skills behaviours

Embracing and leading new digital sectors

AMTC Apprenticeship Programmes and Skills Development – Advanced Manufacturing

A forward facing competency programme, providing a pipeline of future proof talent with digital skills integration

Digital Modular Construction – Level 2 to level 7

An end-to-end learning programme to enable a career path through the construction industry

RIBA (Royal Institute of British Architects) Plan of WorkStage 0 Stage 7

Digital Architect Digital Construction / BIM Technician Automation Technician Modular Assembly Technician

Level 3 - Advanced ApprenticeModular Assembly Technician

AMTC and FE collaboration

Level 2 - ApprenticeshipAssembly Technician


Digital Design Engineer

Level 4 - Higher ApprenticeDigital Construction Technician


Level 6 - Degree ApprenticeDigital Design Engineer

AMTC and HE collaboration

Level 7 - Masters ApprenticeChartered

AMTC and HE collaboration

Construction Manager

Digital Modular Construction

Initial analysis of current standards against digital modular construction

Degree apprenticeship

Design for Manufacture and Assembly

Product lifecycle management

3D modelling / BOM

Offsite Onsite

Digital Design Technician


Initial analysis of current standards

Higher Apprenticeship

4D and 5D modelling

Augmented Reality

Offsite Onsite


Digital BIM Technician



Advanced Apprenticeship

Mechatronic integration, programming and maintenance

Industrial robot integration, programming and maintenance

Offsite Onsite



Automation Technician



Advanced Apprenticeship

Multi-skilled mechanical & electrical etc.

Augmented Reality

Offsite Onsite



Automation Technician

Assembly Technician

MTC Additive Manufacturing: Map the skillsMap the responsibilities of all roles, including their tasks and associated knowledge, skills and behaviour

End-to-end AM process

Productconception

Product suppliedto customer

Design / Sim. EngineerDesign for function, cost,

manuf, inspectionTopography optimization

Design validationQuality Technician

Component inspectionComponent validation

Materials EngineerMaterial selection,

source powdermaterial validation

Materials TechnicianHandling, testing,

storage of materials

Applications EngineerRequirements captureAM process matching

Manufacturing EngineerDesign for manuf,

optimise build,create production pack

Metrology EngineerDesign for inspection,inspection & testing

method selection

Production TechnicianProgramming & operating

of production equip. &post-processing

MTC Additive Manufacturing: Define the apprenticeshipsSteer / influence the creation of AM specific trailblazer apprenticeship standards for each job role(that match competency frameworks)

Applications Eng. Curriculum Design / Sim. Eng. Curriculum Materials Eng. Curriculum Manufacturing Eng. Curriculum

Metrology Eng. Curriculum Materials Techn. Curriculum Production Techn. Curriculum Quality Techn. Curriculum

TrailblazerApprenticeship

Standard


Standard


Standard


Standard


Standard


Standard


Standard


Standard

• An end-to-end solution - Recruitment to Retirement• 16 -18 years old traditional apprentices• 19+ adult apprenticeships• Identification, registration and redeployment.• Upskilling, multi-skilling and re-skilling• Degree Apprenticeships

• L6 BEng (Hons) – Product Design and Development• L7 MSc – Manufacture/Production Engineer• L7 MBA – Senior Leaders Masters Degree Apprenticeship

The AMTC are actively involved in :• Trailblazer Apprenticeship Standards development• End-point Assessment

Apprenticeship LevyThe AMTC Solution

Apprentice Recruitment

Initial Assessment/Diagnostic

Individual/Business Learning Plan

Audit Documentation

Digital Account Management

Sourcing Learning Provision

Delivery of Learning

Managing Learning Quality Assurance

Gateway Support/ Assessment

End-point Assessment

MTC Approved Apprenticeship

The AMTC Apprenticeship Levy SolutionModular Solution

The Advanced Manufacturing Training Centre

The best way to predict the future, is to create it!

The AMTC are creating it!

Thank you