Knowledge-Based Engineering · Technical Specification Statement of Work Logistics Support ISO 29148 Completeness Consistency Correctness Completeness Consistency ... • SCM VIEWS

Knowledge-Based

Engineering

Elena Gallego. Consulting Director at TRC.

All rights reserved © The REUSE Company 2019

Pentagon wars


“◈ It is the idea of knowledge digitalization

one of the challenges that organizations

need to pursue in order to build better

systems or deliver better services, in less

time, with less money and more

efficiency.

3


Knowledge Base Purpose

◈ A few goals of the Knowledge Based Systems are:

⬥ To ensure that the Product or Services development main documents

are Complete, Consistent and Correct

⬥ To support the quality analysis of requirements, models, and

unstructured information or data

⬥ To reuse the Organizational or Domain information among several

projects

⬥ To share knowledge between the different stakeholders in the process

⬥ To infer behavioral patterns from legacy assets

4


Knowledge Framework

5

Knowledge

Management

Traceability

AuthoringQuality

Management

Users

Knowledge Base


40% Cost

Saving(average value)

Constructive Systems Engineering Model - COSYSMO

6


The REUSE Company, deploying services and systems engineering from experience

Innovative technologies applied

to

Knowledge Reuse

7


Product

Oriented

Knowledge Based System: Infers and Uses a Knowledge Base to solve complex problems

Services

Oriented

8


Product

Oriented

Knowledge Based System: Infers and Uses a Knowledge Base to solve complex problems

Services

Oriented

9

01Controlled Organizational and

Project Vocabulary for a common

understanding among stakeholders

Vocabulary

02Recreate and capture the

system architectures

represented in views and

models. Stablish

relationships among system

and system elements

Architectures

04Representation of

assets semantic through

SRL – System

Representation

Language

Formalization03

Represent requirements

similarities and enable formal

representation, automatic

recognition and aid authors

Patterns

05A combination of rules,

tasks and groups to

infer information from

valuable assets

Reasoning


Product Oriented

◈ Product Breakdown

Structures

◈ Architectures

◈ Thesaurus

◈ Patterns

◈ Controlled Vocabulary

Knowledge Organization

Services Oriented

◈ Unstructured data

◈ Unknown inputs of

information

◈ Thesaurus

◈ Patterns

◈ Controlled Vocabulary

10


Different Knowledge Base Applications

Procurement

Product Line

Predictive Maintenance

11

Services

Products


Procurement

Knowledge

Base

12


http://ec.europa.eu/internal_market/scoreboard/performance_per_policy_area/publi

c_procurement/index_en.htm 13


Procurement Knowledge Base Objectives

◈ Automatic Analysis of the Evaluation Criteria

⬥ Traceability between user and business needs and evaluation results

◈ Ensure complete documentation development process

⬥ Guarantee stakeholder priorities are covered at different documentation

levels

◈ Analysis of life-cycle cost among involved areas

⬥ Completeness and Consistency at all levels

◈ Support requirements and models development

⬥ Patterns guidance at all levels

14


Technical Specification Statement of Work Logistics Support

ISO 29148CompletenessConsistency

Correctness Completeness Consistency

ISO 15288 | MIL-Hdbk-245


ASD SX 000iJSP886 | Def Stan 00-600


ISO 29148

Procurement Knowledge Base

15


Quality in context

Completeness

Consistency

Correctness

Completeness

Consistency

16


Correctness Quality Check

◈ The Correctness Quality

Set:

⬥ Characteristics coverage

⬥ Ontology dependency

⬥ Effort needed to fix identified

error

17


Completeness Quality Check

Specification viewpoint Ontology viewpoint

18


Consistency Quality Check

Traces Inconsistency

Specification Inconsistency Ontology Inconsistency

19


PROCUREMENT

KNOWLEDGE BASE

VOCABULARY PATTERNS & FORMALIZATION QUALITY METRICS

• TERMINOLOGY

• NLP RULES

• SCM VIEWS

• CLUSTERS

• PATTERNS

• PATTERN GROUPS

• PROPERTIES

• RELATIONSHIPS

• CORRECTNESS RULES

• COMPLETENESS RULES

• CONSISTENCY RULES

• QUALITY & AUTHORING CONFIGURATIONS

Is formed by

Is formed by

Is formed by

Procurement Knowledge Base main Knowledge work-products

21


Procurement Knowledge Base Organization

22

SSS

Library

CLS/ILS

Library

SoW

Library

PROCUREMENT

KNOWLEDGE BASE

VOCABULARYPATTERNS &

FORMALIZATIONQUALITY METRICS

• TERMINOLOGY

• NLP RULES

• SCM VIEWS

• CLUSTERS

• PATTERNS

• PATTERN

GROUPS

• PROPERTIES

• RELATIONSHIP

S

• CORRECTNESS

RULES

• COMPLETENESS

RULES

• CONSISTENCY

RULES

• QUALITY &

AUTHORING

CONFIGURATIONS

Is formed by

Is formed by

Is formed by

Procurement Knowledge Base


Procurement Knowledge Base Organization

◈ The Procurement Knowledge Base has sub-Knowledge Bases

to cover the three main sort of documents for each of the

knowledge work products.

23

SSS

CLS/ILS

SoW

Each database is developed

by different teams, covering

different content


Knowledge Base Libraries

24

INCOSE

• Guide for Writing

Requirements

EARS

• Requirement Patterns

ECSS

• Domain Knowledge

ISO 26262

• Domain Knowledge

Procurement

• Know-how for Automatic Evaluation


Product Line

Engineering

Knowledge

Base

25


The European automotive sector differed greatly in the level of variety they offered to

customers, although variety had little relation to unitary sales.

BodiesPower

trainsTotal number of variations

European

units sales in

2002

Mercedes E-Class 30 15 3,347,807,348,000,000,000,000,000 157,584

BMW 3-Series 10 20 64,081,043,660,000,000 350,723

Peugeot 206 5 24 1,739 596,531

26

Source: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.469.2061&rep=rep1&type=pdf


Product Line Knowledge Base Objectives

◈ Extraction of requirements from the product-line assets

⬥ Automatic allocation of assets from the solution space to requirements

document

◈ Identification of the variant features in the requirements

⬥ Patterns and Thesaurus to cover commonality and variability

◈ Coverage of the specific system features

⬥ Knowledge interfaces with Product Lifecycle Management software tools

27


The Product Line Knowledge Base is formed by all types of Knowledge

28

Stakeholder

needs and

requirement

s

OperationBusiness or

Mission

Analysis

Maintenanc

eDisposal

System

requirement

s

Architecture

Design

Validation

Transition

Verification

System

AnalysisIntegration

Implementation

Knowledge Base


“◈ The goal of this process is to automatically

generate the right set of patterns to formalize the

features of the products and the different

semantics and values from the natural language

into SRL and later use the formalization of the

different products to generate the variability

model based on the captured features.

29


Operating between assets

Knowledge

QualityModels

Requirements


Ground Operational Amp

<<Connection>

>

Capacitor

<<Connection>

>

Resistor

Operational Amp

Resistor

<<Connection>

>

<<Connection>

>

Operational Amp

Operational Amp

Common Representation Language

Battery<<Message Sending>>

Power Control

SystemCharge System

<<Message

Sending>>

Power Control

System


A simple example of a pattern matching, and relationships generation

When switched on, the Cab radio shall operate within a temperature range of -20°C

to +70°C

When [TRIGGER] and [PRECONDITION], the [ACTOR] shall [ACTION] [OBJECT]

32

Temperature

-20°C +70°C

Operation

Cab radio Temperature


Predictive

Maintenance

Knowledge

Base

33


The Cost of Operations & Maintenance

34

6016

12

12

O&M Tax Management Insurance

85

15

Wind Turbines Rest of the Wind Farm

55

25

20

Spare parts Personnel Consumables

Exploitation Costs O&M Costs Wind turbine Costs


“◈ Combination of a predictive and

preventive maintenance with an efficient

corrective action can save up to 70%

wind turbine operational costs.

35


Predictive Maintenance Knowledge Base Objectives

◈ Automatic failures diagnosis through condition monitoring

⬥ Reasoning engine to identify deviations in data

◈ Representation of legacy data

⬥ Knowledge interface with the data

◈ Predictive techniques to identify behavioural patterns

⬥ Definition of patterns that capture data variations

36


Data MiningKnowledge

Base

Infer data structures

37

Data

Information containers

Information

Set of patterns


93.77%Knowledge Based systems can infer the status of a wind turbine from its

measurements and predict its behaviour in 93.77% of the cases

38


Efficient

application of

Knowledge-

Based

Engineering

39


Make it SimpleProcess automation and User’s Support

40

Systems Engineering Handbook. INCOSE-TP-2003-002-2015 Systems Engineering Handbook. INCOSE-TP-2003-002-2015


Knowledge

Based Systems

to solve complex

problems

Knowledge

Digitalization to

improve the way

we do

engineering

And all this to conclude…

Define the right

strategy to

design and

implement the

Knowledge

Base

41


Thank you!Any questions?

You can reach me at [email protected]

42

mailto:[email protected]



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Knowledge-Based Engineering · Technical Specification Statement of Work Logistics Support ISO 29148 Completeness Consistency Correctness Completeness Consistency ... • SCM VIEWS