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November 25, 2011

Excellence in Asset Management

a Hong Kong example

Albert H.C. Tsang
albert.tsang@polyu.edu.hk

XI Encuentro de Gestión de Activos Físicos Dpto. Ing. de Minería
Laboratorio de Gestión de Activos UC
Campus San Joaquín, Santiago, 25 de noviembre de 2011 Pontificia Universidad
Católica de Chile
www.gestiondeactivos.uc.cl www.egaf.cl

Hong K
H Kong

• A metropolis with a population of 7 million
p p
people
• The major sea port in South China
• A logistics hub in the Pacific Rim
• A center of trusted professional services
• One of the leading financial centers in the
world
• A thriving tourism, convention & exhibitions
industryy
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Hong K
H Kong

Industries with significant investments in physical
infrastructure assets:
• Public utilities – water, power, gas supply,
telecommunications services
• Public transport – train, bus, ferry services
• Port services – airport, airlines, container terminals,
logistics services
• Events & entertainment – convention centers, theme parks
• Financial services – data centers, server banks
• Property management – building engineering services
• Construction industry

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PAS 55
• PAS stands for “Publicly Available
Specification”, a preliminary
standard
• Published by the British Standards
Institution(BSI)
I tit ti (BSI)
• Designed for the management of
physical assets
• Provides a framework for a
systematic approach to
integrating all aspects of asset
g
management
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Asset
A t management requirements of PAS 55
t i t f

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Clause 4.4.7 of PAS 55
Cl 447 f
4.4.7 Risk management
4.4.7.1 Risk management process(es) – must be documented
4,4,7.2 Ri k
4 4 7 2 Risk management methodology
t th d l
• Identify associated potential risks
• Estimate the levels of risks
• Determine whether these risks are tolerable
• Devise risk controls if necessary
4.4.7.3 Risk identification and assessment
• Risk = Probability  Consequence
• Approaches to risk identification – SWOT, HAZOP, etc.
• Risk analysis using tools such as event-trees, fault trees, etc.
event trees,
4.4.7.4 Use and maintenance of asset risk information
• Results of identified risks, risk assessments, and determined controls
should be kept up to date
up-to-date
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Examples of Ri k Management at
E l f Risk M t t

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Risks perceived by
Service Risk : The service criticalities of the railway assets are
ranked on the basis of the potential impact of their failures on
the railway service. The criticality rankings are used for
prioritizing maintenance efforts and improvement actions.
Security Ri k : Th key areas covered include Personnel,
S i Risk The k di l d P l
Revenue/Cash, Premises, Property and Information.
Project Risk : A project risk register is developed for every major
modification and renewal project. The types of project risks
covered include, railway service disruption, health / safety/
environment, cost overrun, programme delay, political/media
pressure, technical difficulty and customer expectation.
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Risks perceived by
Environmental Risk : Environmental impacts such as noise
pollution, water pollution, air pollution, contamination of land
and depletion of resources are assessed and ranked.
Supplier & Service Outsourcing Risk: This covers risks arising
from spares shortage, equipment/technology obsolescence and
f h i / h l b l d
outsourced works.

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As L
A Low As Reasonably Practicable (ALARP) Principle
A R bl P ti bl Pi i l

The acceptability
of a risk is
determined by
human, social &
political
Risk tolerated
considerations, &
only if risk
y
such assessment is
reduction is
made
impractical
subjectively
or grossly
expensive
p

The b
Th boundaries
d i
between the regions
are pushed
downwards with time

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Safety & Service Disruption Risk Matrix

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Safety & Service Risk Classifications

R1 – Safety & service risk must be reduced except in
exceptional circumstances
R2 – Safety & service risk must be reduced if it is
reasonably practicable to do so
R3 – Safety & service risk is tolerable but should be
further reduced if it is cost effective to do so
R4 – Safety & service risk is acceptable

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Environmental Risk Matrix
E i t l Ri k M t i
4 3 2 1
Severity (Scale)
Frequency (No. per year) Negligible Marginal Serious Critical

N/S A/E

Few times per Few times per
A1 week or more ≥100 A2 month or more ≥10 ER3 ER2 ER1 ER1

Few times per ≥10 to Few times per
B1 month B2 year ≥1 to ＜10 ER4 ER3 ER2 ER1
＜100

Few times per ≥1 to Few times per
C1 year C2 10 years ≥10-1 to ＜ 1 ER4 ER3 ER2 ER2
＜10

Few times per 10 Once since ≥10-2 to
D1 years ≥10-1 to ＜ 1 D2 operation ER4 ER3 ER3 ER2
＜10-1

Once since ≥10-2 to Unlikely to ≥10-3 to
E1 operation
i E2 occur ER4 ER4 ER3 ER2
＜10-1 ＜10-2

Unlikely to occur ≥10-3 to Very unlikely to
F1 F2 occur ＜10-3 ER4 ER4 ER4 ER3
＜10-2

Legend: N / S = For Normal Operating Condition or Startup / Shutdown respectively
A / E = For Abnormal Operating Condition or Emergency respectively
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Environmental Risk Classifications

ER1 – Environmental risk must be reduced except in
exceptional circumstances
ER2 – Environmental risk must be reduced if it is
reasonably practicable to do so
ER3 – Environmental risk is tolerable but should be
further reduced if it is cost effective to do so
ER4 – Environmental risk is acceptable

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Clause 4.6 and 4.7 of PAS 55
Cl 46 d47 f
4.6.1 Performance and condition monitoring
461 P f d diti it i
4.6.4 Audits
• Assess effectiveness of the system in meeting the organization’s asset
management policy, strategy and objectives
• Identify corrective actions required
4.6.5 Improvement actions
p
• Corrective & preventive actions
• Continuous improvement
4.7
4 7 Management Review
• Top management shall review the continuing effectiveness of the
management system
• Conducted at regular intervals, such as annually
intervals
• Deficiencies / opportunities for improvement identified as a result of
the management review are addressed, and the AM system is
amended accordinglygy
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System f managing asset management at
S t for i t t t

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Operations Division Balanced Scorecard
Measures and Targets
• Consolidation from OA's CSP, CoMET KPls and business
imperative measures, enhanced connection with OA
i ti h d ti ith
performance and KPls used in CoMET benchmarking
• Connected measures are deployed to Departmental
p y p
Balanced Scorecard
• Methodology for aggregate score is introduced for evaluation
of departmental performance and assessment of achievement
• Clear focus on OA performances
• Clear performance objective: “.. g
p j globally recognized leader..."
y g
• Targets are set predominantly based on relevant plans of the
Division with due consideration of CoMET best performance
level
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CoMET – C
Community of M t
u it f Metros
• Founded in 1996
• Members include metros of Buenos Aires, Hamburg,
g
Hong Kong, London, Montreal, Sao Paulo,
Singapore, Taipei
• Benchmarking & performance measurement of
Metros
•CCase studies are conducted to id
di d d identify b
if best
practices

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A sample of C
l f Case St di U d t k b C MET
Studies Undertaken by CoMET

• Rolling stock procurement
• Security in stations and trains
y
• Asset condition monitoring
• Energy saving initiatives
gy g
• Infrastructure possession management
• Track Performance in snow
• Economic life of assets

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Performance Management Framework

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Cascading Measures
g
an example: Service Quality

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Strategic Goals
St t i G l
S1 Passenger Injuries Requiring Hospitalization C3 Train Service Reliability (kkm per 5-min)
Rate (12-month average) C4 Complaints on Operational Issues per
S2 Passenger Injury Rate (12-month average) Customer
S3 Staff LTI Frequency Rate (12-month P1 % Coverage of Scheduled PM
average)
P2 Response to Failure
S4 Contractor Safety Reportable Accident
Rate (12-month average)
(12 month P3 Operations Project Completion Rate (YTD)
S5 Risk Control Performance Index P4 Self-monitoring on Environmental
Performance
S6 Passenger Crime Rate (12-month average)
P5 Pax-km per OD Staff ’k
F1 Di i i
Divisionall C t per th
Costs thou P k
Pax-km P6 Operations Energy
F2 Divisional Costs per Revenue Car-km P7 Direct Job Cost Ratio (to be reported
F3 Station Commercial Income per quarterly)
Passenger
L1 Training Hours Ratio
C1 Customer Service Pledges Score L2 Total No. of Contributions of MTR Creators
C2 Passenger Affected Ratio Communities (to be reported quarterly)

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Excellence in Asset Management
E ll i A tM t

plays a crucial role in enabling
organizations with significant
g g
investment in physical infrastructure
assets to achieve
sustainable business success

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See you at ANQ 2012 in Hong Kong

www.ANQ2012.org
g
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THE SPEAKER
Albert H.C. Tsang is a long serving faculty member of the Department of
Industrial & Systems Engineering at The Hong Kong Polytechnic University. He
has a PhD from the University of Toronto. Dr. Tsang is a registered engineer
with working experience in the manufacturing industry covering functions such
as industrial engineering, quality assurance, and project management. He is a
founding member, fellow, and former Chairman of Hong Kong Society for
Quality. Dr.
Quality Dr Tsang had provided consultancy and advisory services to
enterprises and industry support organizations in manufacturing, logistics,
public utilities, health care, and government sectors on matters related to
quality, reliability, maintenance, performance management and assessment of
performance excellence.
Dr. Tsang is the author of “WeibullSoft”, a computer-aided self learning
package on Weibull analysis and three of the books he authored are related to
analysis,
engineering asset management. One of these books is “Maintenance, Reliability
and Replacement: Theory and Applications”, the reference text of a course he
delivers in Peru, South America.
Católica de Chile

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