Digital Readiness Level (DRL), Simon Barnes

H S S M I © 2 0 1 6

Digital Readiness Level (DRL)

Collaborate. Innovate. Deploy.

Our MissionAs an independent institute, we collaborate

with manufacturers, other academic

institutes and solution providers to

deploy innovative technologies,

tools and methods to support

the manufacturing

sector.Our

VisionTo lead in providing

outstanding value and

knowledge for sustainable

manufacturing


Our Members & Stakeholders

OEMs

Universities

Solution

Providers


Virtual Engineering

Data Analytics forResource Efficiency

Circular Value Chains

ManufacturingNew Technologies


How has we the concept developed?TO DATE:

• Talked to stakeholders, both industrial and academic

• Held a workshop through the Digital Engineering and Test Centre Programme (DETC)

• Refined through contact and internal workshops

• Engagement with the Digital Catapult (Manufacturing is a key work stream)

NEXT:

• Create a wider steering group

• Gain greater support and mass

• Feedback loop

• Qualitative testing of the model


Digital Readiness Level (for manufacturing)

Vision:

• To provide UK Manufacturing with a consistent technology and process based measure to assess the digital preparedness of a company or production facility

• A design a measure that is widely applied and utilised based on sound research and experience

• A measure that challenges toward the best, irrespective of size (or sector), and delivers with a fast pace of change


Digital Readiness Level (for manufacturing)

Objectives:

1. To give context to the Industry 4.0, Factory of the Future, Digital Manufacturing landscape to a wide range of manufacturing businesses

2. To create a clear platform for communication – digital needs consistency of language and style to be understood, discussed, interpreted, developed and deployed

3. To identify value from digital in manufacturing – focus to deliver the productivity and process improvements of up to 20 per cent generically discussed

4. To be seen in the same capacity as Technology Readiness Level (TRL) and Manufacturing Readiness Level (MRL)


How might the model work

The model will focus on a manufacturers:

A. Capabilities – Are the core capabilities needed to support Digital Readiness present?

B. Competencies – Are certain competencies demonstrated under each capability as evidence to support that capability?

C. Evaluators – A set of questions to assess competencies

Delivering a summary – a concise, key phrase development of each stage of Digital Readiness Level (DRL)


Capabilities

In its work so far HSSMI has identified six capabilities that combine to develop a platform for Digital Readiness, these are:

1. Development of the business case process

2. Technical capability technical

3. Data management technical

4. Leadership process

5. People process and technical

6. Systems integration technical

These are a balance of process and technical – we need to assess to ensure we have got this balance right


Competencies

4. Leadership

A. Strategic direction

B. Partnerships for development

5. People

A. Skills and upskilling

B. Culture

6. Systems Integration

A. Supplier engagement

B. Customer engagement

C. Internal integration management

1. Development of the Digital business case

A. Identifying value from Digital

B. Commercialising benefits of Digital

2. Technical capability

A. Development and testing tools (virtual)

B. Equipment infrastructure (physical)

3. Data Management

A. Data usage strategy

B. Ownership and control of data

Within each of the capabilities two or three competencies have been identified to support the capability:


Developing DRL

Through or work at the Advanced

Propulsion Centre Digital Spoke

we have a set of inputs that will

help HSSMI define the

competences and question sets

for Digital Readiness Level


A progressive and parallel change in attitude

1. Development of the business case

2. Technical capability

3. Data management

4. Leadership

5. People

6. Systems integration

1 2 3 4

Readiness

levels are

based on

business

challenges

and can be

used to

highlight and

action issues

horizontally,

they are not

system or

vertical

based

system

approached

Awareness of

machine data

Full machine

connectivity

All resources

linked

Machine and

assets connected

External use of RFID

track & trace

Links to Suppliers

in place

Prognostic

maintenance


Examples of Value - People and Data Management

New skills (IT, programming,

Virtual tools)

New ways of working –

Collaboration internally and

externally

Companies to be attractive to new

employees from other sectors

Data sharing between various

departments

Data sharing with the supply chain

New approach to data protection whilst

still maintaining confidentiality and IP

security

Value of data / information becomes

more important

“Data only” companies will enter

manufacturing


Examples - stretching the Technical Capabilities for Digital

Level 1: Data capture – Capture of data related to machines,

production performance, facilities and operator across the

value chain

Level 2: Connectivity and visualisation – Connect the relevant

data to create a “single source of truth” / digitally map the

production processes with the digital representation

Level 3: Interpretation – big data, data analytics for production

planning, maintenance, training

Level 4: Pre-emptive decision making / new business

opportunities – production scheduling, “self-healing” or self-

maintaining system, …

15

Comparison of dimensionsNon technical dimensions

Strategy and organisation

• Strategy

• Investments

• Innovation management

Employees

• Employees skill set

• Skill acquisition

Leadership

• Strategic direction

• Partnerships

People

• Skills and upskilling

• Culture

Development of the business case

• Identifying value of digital

• Commercialising benefits of digital

I4.0 readiness model Digital readiness model

16

Comparison of dimensionsTechnology dimensions

Smart factory

• Digital modelling

• Equipment infrastructure

• Data usage

• IT systems

Smart products

• ICT add-on

functionalities

• Data analytics in usage

phase

Technical dimension

• Development and Testing

• Tools and Technology

Data management

• Usage of Data

• Ownership and Control

System integration

• Supply chain engagement

• Customer engagement

• Internal integration

I4.0 readiness model

Digital readiness model

Data-driven services

• Data driven services

• Shares of revenue

• Share of data used

Smart operations

• Cloud usage

• IT security

• Autonomous processes

• Information sharing


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