Enn530 Asset And Facility Management-Management Assessment Answers

Answer:

Electricity distribution is a complex system, which involves high-risk management. Its process requires an Asset Management Plan (AMP) with a risk profile of each of its asset levels (Haines & Hodkiewicz, 2014). A reliable plan needs a quality maintenance model and a capability model that monitors the processes, functions and measurements. As an integral part of asset management, it has a risk-based life cycle. A report by PWC on financial reporting for power and utilities acknowledges the need for constant research and monitoring of power and utility activities (PWC, 2011). The critical pillars for improved power usage are the real assets and their components. These include the transformers, cables, towers, overhead line wiring system and the switchgear.

The maintenance issues in this system include maximized performance, replacement and reliability issues. ISO 55000 and the ISO 14224 present global standard policies for asset management to ensure a continuous and growing network (Shin & Jun, 2015). These motivate financial efficiency, process viability, risk management and improved services. Computerized Maintenance Systems ensure efficiency in the power generation process through the prevention of impairments, and transmission failure. Using standardization as a better process of data management and strategy, this discussion focuses on the transformer asset and electricity distribution processes, control, maintenance and distribution management.

Asset management is unique for different industries and companies (GHD, 2014). The Asset Management Council (ACM) defines asset management with a focus on asset integrity, its functionality, safety, leadership and skills (The Asset Management Council, 2017). An asset management process needs a plan that involves a management policy, strategy objectives and maintenance and delivery plan.  This is critical because an effective asset management reduces the rate of failure within a distribution life cycle (Quezada, Szatow, & Liley, 2012). It captures the network performance, its capability and reliable modes. It is also instrumental in cost effectiveness because of the improved distribution. Fixed assets include the property, plant and its equipment. Asset components include the distributed assets namely the transformers, cables, overhead lines, switchgear and towers. The service components include the distribution, utilization, operational design, costs and strategic planning as shown in the figures below.

Asset Management Capability Models

Kerry & Robyn (2015) specify that asset management thrive on a capability model framework. The Asset Management Maturity Model (AMCaMM) is an integrated system with different processes and levels of a capability indicator. The electricity power distributor depends on a distributed generation (DG) system, which has clearly defined capacity units, appropriate location, type of network and technology used (Khatod & Viral, 2012). This model supports a continuous supply system to meets the growing demand. Research points out that Australia’s energy intensive demands call for a reliable energy supply that goes beyond the costly blackouts and peak hours (Kerin, 2014). This means a synchronization of total assets like generators and structures in the electricity distribution system such as poles and wiring systems.

Suwnansri (2014) identifies the transformer as a major asset in electricity distribution. This is a vital link in the electricity distribution network because it affects the life cycle process. Its maintenance issues include visual inspection, electrical tests, unstable system, damage and failure. The figure below points out the central role played by transformers in the electricity storage and distribution process.

Asset Management Delivery Model

According to Stirna, Grabis, Henkel, & Zdravkovic, (2012), the evolving organizations today need a capability driven approach to service delivery. This is an integration of the organizational growth and development process with its Information Systems (IS). The figure below shows a summary of a capacity delivery model for a continuous improvement process. This approach advocate for the use of appropriate technical, business, financial, risk based and operational plan in the processes. It identifies performance indicators and the business capability within a specific context. In this case, an organization focuses on the service demand, system engineering, configuration, acquisition, operational and maintenance as well as continuous improvement processes (Siano, 2014).

Asset Management Excellence Model

The maturity of an electricity distribution network stems from a cycle of growth. Located in South Eastern Queensland, Energex Ltd exits in a mature market landscape controlled by the government. With a market share of 15.5%, the government owned company boasts of assets in $13.3 billion and a distribution network of 25,000 square kilometers, which covers remote as well as densely populated regions (Energex, 2014). The Energex power distribution network faces threats such as the rapid adoption of solar systems as alternative energy usage. Capability models provide guidance on software input with safety and environmental concerns. The installation of technology systems at the poles, wiring systems, transformers and substations determines the mechanism of the flow, supply and consumption at the accumulation meters as well as the specific electricity demand. That is why Ahlemann, Stettiner, Messerscmidt, & Legner ( 2012) suggetst that the Asset Management Excellence Model is a type of AMCaM with a wider dimension of the critical processes. This data systems approach evaluates various options such as the delivery, operational (equipment) governance, knowledge management and risk management as shown in the table below.

The figure above shows an asset management model based on costs of introducing data management approaches to one asset or a complex unit and the development of varied scenarios in a lifecycle. The electricity distribution network keeps evolving over time as determined by the supply and demand in a capacity-based process (AtKearney, 2011). Operational excellence starts with systems set up and develops a maintenance plan within the lifecycle cost and performance indicators. Service providers depend on strategy for an appropriate direction on efficiency control and maintenance (Porter & Tanner, 2012).

 IQM-CMM (Information Quality Management-Capability Maturity Model)

 Gonzalez, Fernandez, & de la Pena ( 2016) agree that advanced technology aides the distribution and transmission processes through improved reliability of assets. Quality maintenance leads to improved perfomance and asset management at critical points of an electricity distribution process. using quality engineers, optimization of asset management and improved asset health require advanced algorithms that control failure rates and circuit breakages.

 The Digital Asset Management (DAM) Maturity Model Version 2.1

The DAM model is an optimization of the processes at a competency level involving people IS and processes. This systems model acknowledges stakeholders involved as drivers in an asset management plan. It highlights their benefits and techniques. It looks at the teams involved and the service delivery models without ignoring the role of quality management and continuous improvement (Cameron, 2011). In this approach, the technical expertise compliments the streamlined functions through organized workflows and integration points. Its areas of focus are the infrastructure, and the hierarchical structures featuring the people, information, systems and process management (Bradley, Li, Lark, & Dunn, 2016)

Summaries of Model Deficiencies and Comparisons

The incorporation of an IS into a process or organization is a strategic plan. The DAM model helps an organization to define its competitive edge because it highlights the unique attributes of an organization into unique levels with 4 categories and 15 sub classifications (Pearlson, Saunders, & Galletta, 2016). However, it needs a structural or eco system and it builds on other models. IQM-CMM emphasizes on quality in information for economic productivity. It has a high focus on accuracy and robust systems. This becomes a limitation because of the high standard definition of quality, which applies to different industries and is more costly (Reichert & Weber, 2012). The Asset Management Excellence Model is an optimization approach for financial, risk, compliance and service output. It enhances a brand’s image and it improves stability. Hill, Jones, & Schilling (2014) discuss how different organizations thrive under different conditions because they have different modes of strategic approaches. The use of Asset Management Capability Delivery Model concentrates on efficiency at the expense of other optimization factors like quality and management practices (Kwon, Lee, & Shin, 2014).

Asset Management Capability Model

Asset management is a systematic approach to maintenance, upgrading and operating tangible and intangible assets (Cosic, Shanks, & Maynard, 2012). Globally, the government spends a considerable amount of money on electricity distribution systems. However, there are challenges such as:

• Aging infrastructure
• High cost of electricity outages
• Unexpected risks such as weather effects
• Reliability in electricity supply

Asset Management Processes

 Electricity generation depends on natural resources and it has complex supply and demand factors. Constant changes in the market system also requires regular maintenance and upgrades to meet the growing demand. The Asset Management Capability Model provides an optimization approach for a multilevel system in a dynamic industry (Igor, Kyeong, & Bae, 2012).  Asset management needs and infrastructural development for a sustainable service delivery process (Mezger, 2014). It creates a competitive advantage whose system personnel, procedural and technological implementation has a holistic approach. Asset management connects business, technology and economic objectives of an organization. As an information system, it provides a logical approach for lifecycle delivery, asset management strategy and planning, risk and knowledge management.

The ISO 55000 is a global feature of asset managemet system that works with different assets to provide technical specifications on the improvement on an assset base, improvement, implimentation plans (ISO, 2014). The ISO 14224 is a maintenance system for best practice procedures and distribution networks. It provides analytics for equipment and power distribution for event analysis (Oshiro, 2017). Contemporary asset management strategies rely on data based maintenance that adheres to international standardization. It covers safety standards, risk management, lifecycle costs, reliability and maintenance and failure rate analysis.  Applied within the planning, system design, implimentation and constant reviews, it guides service providers on the best asset management approach (ISO, 2014). Asset management capabilities define the system through its asset lifecycles. The framework below highlights the connection between business and asset lifecycle. Compliance to the ISO 55000 value delivery adds value to the delivery process for reliability and excellence.

Baggen, Correia, Schill, & Visser ( 2012) identify the importance of data collection as a way of failure identification in equipment use, failure modes and safety impact of a process. This analysis provides appropriate information on the mechanisms required for the improvement of the functions. It highlights the subcategory failure and components through a detection mode. It also paves the way for conditioned management of failure in mechanisms and plant safety. Quality systems with international standardization provide additional information such as date of failure and impact on the plant operations (Baggen, Correia, Schill, & Visser, 2012). Reliable diagnostics provide leadership and policy strategy for minimization of future failure rates as shown in the figgure below.

Asset Management Functions

Teece (2012) discusses an asset management system in a routine program that manages by monitoring and maintaining. This is a systematic process operating in its professionals and legal framework. Asset management is a response to the changing market environment and organizational needs for internal and external resource management. In order to serve multiple benefits in an IT system, an asset management software needs an integrated approach to functionality for the highest possible outcome (Brown, 2016). Having a clear definition of the type of failure identifies gaps in the maintenance process for quality improvement mechanisms. Figure 7 shows the process of asset management in an electricity distribution process includes reliability, risk management, company objectives and data driven process management. Is case, asset management includes management across the organizational functions such as:

• Asset tracking
• Work flow tracking
• Supply chain management
• Finance system
• Information systems

Asset Management Software

According to Peppard & Ward (2016), software systems provide solutions in asset management for low cost integration of IT and business objectives within the asset lifecycle. This means the installation of IT systems across the planning, requisition, configuration, repairs and relocations among others. Different assets require specific strategies for its asset lifecycle. IT asset management supports compliance, configuration, and control objectives. Organizational assets include policies, procedures and technologies.  Figure 8 below illustrates how an asset tracking software analyses the asset operations and service delivery for effective maintenance (Symphony Summit, 2017). It provides a simple implementation process that has a routine methodology and a predictable plan for managing assets in an organization or industry. Challenges arise in the implementation of measures in specific assets because of the varied measures required for the improvement and maintenance processes (AtKearney, 2011).

Security Challenges

Electricity distribution companies like Energex face security threats in transmission, generation and distribution of electricity. Threats to asset management at the controls, transmission lines, communication system and operational levels affect the service delivery process (Subashini & Kavitha, 2011). Effective asset management facilitates for effective monitoring and repair on faulty equipment and assets. Control systems within the Asset Management Capability Modelling enhance capabilities by predicting and identifying gaps in new infrastructure. IT systems also improve security through service risk management and data protection at the implimentation, multi ranking and cloud security systems as shown below (Ernest & Young, 2017). The electric energy system needs an analysis and operational system that facilitates for security, reliability and stability. A network for improved distribution management and scientific data bases, the asset management software applies security risk management across the risk factors (ECCI, 2015).

Asset Performance Measurement, Evaluation and Improvement

Global concerns for ecological awareness raise the need for energy efficiency and environment friendly processes (Bunse, Vodicka, Schonsleben, Brulhart, & Ernst, 2011). Government procurement, production processes and services incorporate cleaner energy in global warming. Sustainability as a major concern in industry development and it calls for new and improved ways of doing things in line with the contemporary challenges. Asset management in the manufacturing, production and delivery processes require a green energy need system. Kurien & Qureshi ( 2011) illustrate the capability management model as a process of monitors and controls in the supply chain for this efficiency. 

Condition Based Maintenance (CBM) approach such as the Time Based Maintenance (TBM), which is ideal for the prevention of degradation. It predicts breakdown and offers diagnostics for monitoring failure. This lowers uncertainties to ensure constant power supplies. It is also an optimization model that enhances productivity. However, its limitation indicates high costs of acquisition and maintenance and technical challenges of accuracy and diagnostics (Shin & Jun, 2015). The use of smart grid performance in business design ensures that the utilities and public service distribution units overcome capacity challenges in the installation and operational units.

 Rummler & Brache (2012) point out that the Asset Management Capability Model has an integrated approach, which focuses on performance improvement at the asset and group levels. The continuous innovation process advocates for strategic modelling that optimizes on capabilities. Through configuration, an integrated system incorporates intelligent replacement, performance, maintenance and risk management systems in its monitoring and control power units. Allan (2013) acknowledges that assets in such systems require a reliable planning, and asset management approach for increased investment. Important asset management points in the generation of electricity are the transition, distribution as well as the consumption levels as illustrated below. Restructuring the power distribution unit calls for efficient asset management capabilities of the current model and possible plans.

Further improvements include global standardization elements. In support of the ISO55000 and ISO14224, the ISO 28000 identifies the importance of security measures in the supply chain for controls and continuous improvement (Simon, Karapetrovic, & Casadesus, 2012). Complex systems need a paradigm shift and the evolution of the ISO standardization shows continuous improvements for the industry. Asset management through condition improvement in a complex system captures the cost and priority factors of a system (Zhu, Sarkis, & Lai, 2012). The Queensland government carries out an evaluation of the energy needs before building a reliable framework that is capable of meeting the performance needs. The performance measures dictate the constant improvement on the capability models for effective asset management approaches.

Data Collection Methodology and Tools

The extensive literature review focused on real life case examples and academic research. The extensive research provides an analysis of the asset capability models.  This critical analysis of the management approaches leans towards complex data management and the lifecycle of asset management. It carries out a comparison of the Asset Management Capability Models in order to identify an integrated approach suitable for the contemporary approach. A summary of the models points at the pros and cons. A major focus on the Asset Management Capability Model    unfolds the significance of these models in the industry, power generation, collaborative innovation, routines and integrated systems.

The secondary data analysis considers journal articles, books, reviews, online resources and conference proceedings. The use of case study analysis provides a deeper discussion on the specific models and the practical use in a large organization. The secondary data includes research findings from primary data collection and secondary research. An analysis of data base designs simplifies the model categories for better comprehension. The data collected includes information from the Australian government and private organizations as well as local and global publications.

The research sought to discover critical factors in the asset maintenance, product demand, efficiency, reduced wastage, energy efficiency and the technical skills required. The expected outcome was to analyze maintenance activities and their contribution to efficiency. It also brings out the importance of having systems upgrades in line with the organizational, industry and global standards. The study looks at an integrated approach in which predictive models, preventive and reactive methods come into play for risk management, cost effectiveness and efficiency.

The project asks the following questions:

• What asset management actions are appropriate for the electric power distribution system?
• What risk management approaches are effective in asset management for a contemporary power distributor?
• Are these asset management strategies compliant with ISO 55000 and ISO 14224?
• What improvement mechanisms are reliable for a large-scale power distributor?
• What are the advantages and disadvantages of innovation in asset management?
• How can an organization incorporate environmental and safety factors in asset management activities?
• How can a distributor assess the data of an asset life cycle?
• How can the maintenance and monitoring strategy include the ISO 14224?

In the end, the project hopes to address the following objectives:

• To management network risks, cost and performance outcomes in a power distribution channel.
• To incorporate ISO 55000 in the improvement of asset life cycle management, asset data and information breakdown.
• To incorporate contemporary technology in the electric distribution network for best practice and improved customer service.
• To maintain and improve the Life cycle of Assets in line with the ISO 14224 standards.
• To ensure that the asset management activities are environmentally sustainable throughout the asset management process.
• To reduce the failure rate of asset management life cycles.

From the research questions, an electricity distribution company needs to include efficiency  as an asset management plan. It reduces the cost of electricity distribution through less power usage for reduced maintenance expenditure. It is also evident that upgrading the Energex systems also affects the customer servive. Innovation is a contninous process that involves the installation of an upgrade or improved features. This project also identifies maintenance activities as multilevel and multifaceted in a power disctribution network. It also acknowledges that scheduled maintainace prevents the rate of failure and that datasheets improve the lifecycle of energex capability models by preventing mistakes and controlling the outcome. It also points at the transformer as a critical asset in the network.

Using the company’s tripple lifecycle strategy for asset maintenance an mangement team is able to identifies a transformer asset failure through a prediction of oil spillage or potential failures. Asset Capability Models identify the condition of the assets, perfomance and risk failures. It also has a mechanism for preventng unacceptable conditions through a corrective and replacement process. Finally, the company’s reactive method utilizes the risk and cost factors. This makes it reliable for the high population and it has low chances of failure.

The transformer as the central focus needs a continous management process that captures the industry’s and regional power supply needs. Its regular operations and maintenance should be within the cost factors. Optimization equipment protection and automated controls are important in checking the plant reliability, possible risks and costs respectively. The scheduling process compliments different phases of the cycle as shown in figure 16 below.  Figure 17 highlights how to monitor the frequency of failure rates.

Energex asset monitoring policies support the ISO 55000 in support of critical processes for quality asset management. Its life cycle comprises of the following:

• Procurement for repair parts in the system
• Planning for new projects, monitoring and maintainance
• Design of an innovative system
• Construction of distribution substations and asset locations
• Network Operation for the central and susystems
• Refurbishment of aged networks and outdated systems
• Analysis of the operation ability of the asset and rate of failure

The plan also has asset replacement, retirement as well as disposal mechanisms. It is also evident that Energex is keen on adopting asset management plans that enhance capability as well as the organizational objectives. Merging these components of a complex model that meets the assets perfomance measurements, evaluation and impovement.

 management is critical in the electricity distribution process. It ensures a sustainable and continuous process that meets the growing demand. However, an effective asset management plan is necessary for a power distribution network.  A reliable model needs a standard of quality and that supports viability, risk management, sustainability and efficiency. This project considers the power distribution case study in order to find out more about asset management in a network risk management, cost and performance controls under the electricity distribution network.

It looks at Energex Limited, which is located in Queensland as a growing network in need of a reliable asset management plan. Located in a busy region where energy use is on the rise, Energex represents a high optimization system dedicated to quality networks with high security standards. Energex annual report ( 2016) identifies the limitations within its substations including transmissions, and feeders. Among these are:

• cost factors
• load overflows
• replacement
• refurbishment
• upgrade and
• introduction of alternative feeders

limitations in substation equipment such as transformers present maintenance challenges.The company shows multipe gaps in the refurbishment process raising the need for improved standards. According to the report, Energex also needs proper monitoring and operational strategies that can forecast the transofrmer loads while monitoring growth.

From the Energex Planning Reports (2017) the company has electric and magnectic fields located in South East  Queensland. The company policies indicate the importance of reliability, safety and costeffectiveness. As part of the policy plan the company also has a sustainability appraoch that caters for environmental concerns. The company is also keen on avaoiding conflict of interest and risk management. Other policy priorities also include the health and safety plan, public interest and quality. These are critical issues forming Energex objectives and important perfomance factors in asset management.

 Improvement Plan

Assets in electricity distribution undergo lifecycle management in order to improve, repair or replace them (Wang, Vandermaar, & Srivastava, 2002). These repairs include internal and external elements which if ignored pose a risk to the utility. Risk management in this case includes checks to prevent the rate of failure. Preventive measures include routine checks and regular testing. The condition-based maintenance covers the equipment, plant networks as well as the electricity distribution networks. Proper diagnostics through technology tools identifies these gaps through internal monitoring systems for timely fixes. Predictive analytics is an asset management approach that checks the capabilities of a system through data mining, in order to avert uncertainties. This happens through data readings on equipment performance, process analytics, instrument performance, computerized maintenance, and control of distribution (Assertivity, 2017). Different asset management models are favorable to different assets and functions.

Short Term plan

Energex Queensland represents a complex structure in a complex industry. Successful implementation depends on various factors including past performance and process optimization factors (Lin, 2007).  Before upgrading an asset in a complex network, it is important to consider the outcome as well as future calamities such as power outage from extreme weather conditions. From the findings, Energex has a concrete asset management life cycle. Its threefold mechanism is integrative and tries to resolve common asset management needs in an electricity distribution industry. Asset Management Capability Models provide solutions for checks and balances across different capability frameworks. An integrated approach with captures the asset functions processes and its improvement needs (Hill, Jones, & Schilling, 2014). By taking data based analyses, the competent system makes diagnosis, predictions, and reactions on appropriate measures for the organization. A closer look at the pros and cons of the models identifies an integrative system as ideal for a complex system like Energex. This approach considers critical areas of each subcategory to fill up the existing gaps across a whole system. It is able to address the daily and peak power distribution challenges through the simulation model.

 Long term Plan

The project further identifies the ISO 55000 and ISO 14224 as appropriate data and information management systems for a complex data system because of the risk based approach (Goerdin, Mehairjan, Hanea, Smit, & Van Voorden, 2015). Effective data forecast of the land area identifies substation needs for proper transformer needs. When this fails, the capacity of the electricity generation diminishes. The asset management capability has a modeling approach that makes recommendations for appropriate supplies within the Energex localities in Queensland. It highlights proper percentages for its domestic load category. Inaccurate readings pose a great risk to the environment and the equipment in use. Proper limits for electricity supplies within the domestic and commercial settings is also a priority.

Using the electricity power distribution as a case study, this discussion brings out the modernization of asset management approaches for improved services. (Ang, Choong, & Ng, 2015). Asset management capability involves the use of models for reduced rate of failure in a life cycle and it adheres to environment friendly tactics for sustainability. As a national, distributor the company needs to show its commitment to eco-friendly approaches. By agreeing to the National Electricity Rules for Queensland, the company ensures that its project installations and repairs are safe, reliable and effective on costs (Energex Planning Reports, 2017). The ISO 55000 supports this through its distribution plan that has regular updates. These ensure customer satisfaction through a stable electricity supply. Recent development to digitize its customer service through mobile communication is indication of the continuous process of innovation.

The Energex Planning Reports (2017) indicate the company’s commitment to reduce risks  and service failures through an emergency service. This makes the Digital Asset Management Maturity Model an ideal tool for monitoring this. It controls electric shocks and reports details of fallen powerlines or faulty generators under its emergency segments. The inveolvement of the customer in this National framework makes the asset management more complex because it serves millions of customers in different locations. The effectiveness of IQM-CMM ensures that there is quait maintenance across the assets. In order to reduce costs  implication of implmenting this communication model, the comopany uses affordable channels such as social media. Understanding the network system makes implimentation easy hence this calls for training of the staff. Igor, Kyeong, & Bae (2012) supports distribution planing that captures the structural framework. This means that Energex needs to take a leadership  role in asset management for other non government investors. As a public company, it has objectives that serve the public good. This makes value addition a critical factor of measuring the asset capability management process.

 Recommendations

From the analysis, the predictive capacity of an asset management system lies in its risk management model. Further inquiry into this factor is necessary due to the contemporary risks involved such as cyber systems. The predictive risk analysis determines the risk profiles for each of the assets. This ensures that the transformers operate in accordance to the ISO14224 as well as other inputs. Asset Capacity Management Models are therefore crucial in the decision making process.

It is also important to note that the review acknowledges the fact that each of the assets is different. This calls for unique solutions in accordance to the specified needs. The use of a general approach as stated by the Energex Asset Cycle Management Strategy presents limitations in varied capacities. The Asset management Excellence Model supports optimization of the key performance elements. Splitting this to different assets is one way to ensure that the solution addresses the important measures in an asset.

Energex is a government organization, which may have different business models from a private organization. Although Energex addresses cost factors as one of its challenges, it faces complications of adopting high optimization asset tools and devices, for higher revenue returns. This point towards its limited predictive, reactive and preventive methodology. The company may neglect financial risks, which are contributing factors to system upgrades and failures. Thus, the relevance of technology is not limited to the three categories enlisted by the company. Competitive advantage is also a significant element adopted by government organizations.  

Energex shows a gap in proper assessment plan within its asset life cycle program. This calls for an optimization process that shows the projected refurbishment as well as replacement expenditure profile covering each of the assets. This contributes to the development of a reliable ERP model such as PREDI. This is an innovative software, featuring a unified data flow for to all its assets.

The Energex organization needs an advanced distribution system with an asset management system that is easily accessible. This allows customers and stakeholders to access accessible appropriate systems times for convenience and emergency response.  This means that the crew and operator can access systems as much as consumers can utilize mobile communication.

Managing assets through reliable management plans within the annual or five-year plans may not be viable because of the continuous process of change. Innovation is dynamic and unpredictable. Asset Management capabilities Models and professionals handling process need to upgrade constantly. The company needs a flexible plan that accommodates for disruptive technology in the industry. In order to gain a competitive edge, Energex needs a customized approach to asset management. Finding a smart approach that gives the company a unique approach with high efficiency and cost effectiveness remains a challenge.

 Conclusion

Finally, the asset management procedures in an electricity distribution unit is complex. An analysis of large companies such as Energex, AGL and SA Power Networks reveals these complexities intertwined in the functions, processes and performance measures. From the results, it is evident that aligning the real life case to the asset management models is a challenge, which needs a holistic approach. Therefore, evaluating the utilities is necessary to ensure that the power distribution network does not fail. Regular maintenance for replacement and upgrade of the old systems indicates the constant need for change in innovation.  

Therefore, the implementation of an asset management model is flexible and subject to change in accordance to industry changes. The location of an electricity distribution system is also critical because of varied rules and standard regulations such as safety measures. The case study considers the electricity distribution system in an Australian based power company. Located in Queensland, it falls under its local jurisdiction and its asset management procedures follow the companies and national specifications. This is a developed country and companies like Energex, AGL and SA Power Networks stick to international standards. Among this is the sustainability and environmental laws which ensure energy efficiency and green approaches.  The use of different asset management procedures increases the complexity of such a large system complex creating the need for advanced technology.

References

Ahlemann, F., Stettiner, E., Messerscmidt, M., & Legner, C. (2012). Strategic enterprise architecture management: Challenges, best practices and fuure developments. Springer Science & Business.

Allan, R. N. (2013). Reliability evaluation of power systems. Springer Science & Business Media.

Ang, B. W., Choong, W. L., & Ng, T. S. (2015). Energy security: Definitions, dimensions and indexes:. Renewable and Sustainable Energy Reviews, (pp. 1077-1093).

Assertivity. (2017). Current Use of predictive analytics in asset. Asset Management Consultants. Retrieved October 30, 2017, from https://www.assetivity.com.au/article/maintenance-management/current-use-of-predictive-analytics-in-asset-management.html

AtKearney. (2011, October). Reaching Peak O & M Perfomance in Power Generation. Retrieved October 24, 2017, from ATKearney: https://www.atkearney.com.au/en/utilities/ideas-insights/article/-/asset_publisher/LCcgOeS4t85g/content/reaching-peak-oam-performance-in-power-generation/10192

Baggen, R., Correia, J. P., Schill, K., & Visser, J. (2012). Standardization code quality benchmarking for improving software maintainability. Software Quality Journal, 20(2), 287-307.

Bradley, A., Li, H., Lark, R., & Dunn, S. (2016). BIM for infrastructure: An overall review and contructor perspective. Automation in Construction, 139-152.

Brown, R. (2016). Reliability and distribution asset management. Retrieved from Electric energy online: https://www.electricenergyonline.com/show_article.php?article=179

Bunse, K., Vodicka, M., Schonsleben, P., Brulhart, M., & Ernst, F. O. (2011). Integrating energy efficiency performance in production management-gap analysis between industrial needs and scientific literature. Journal of Cleaner Production, 19(6), 667-679.

Cameron, S. A. (2011). Enterprise content management. British Informatics Society Limited.

Collins, D. (2012, August 21). DAM promising: Collaborative innovation meets digital asste management . Retrieved from Innovation management: https://www.innovationmanagement.se/2012/08/21/dam-promising-collaborative-innovation-meets-digital-asset-management/

Cosic, R., Shanks, G., & Maynard, S. (2012). Towards a business analytics capability maturity model. ACIS 2012: Location, location, location: Proceedings of the 23rd Australasian Conference on Information Systems 2012 (pp. 1-11). ACIS.

ECCI. (2015). Supply Chain Security. Retrieved from ECCI International: https://www.eccinternational.com/consulting/standards-and-compliance/supply-chain-security-

EIA; . (2012, June 29). Today in energy. Retrieved from Energy Information Adminitsration: https://www.eia.gov/todayinenergy/detail.php?id=6910

Energex. (2014). The power behind South East Queensland. South East Queensland. Retrieved October 23, 2017, from https://www.energex.com.au/__data/assets/pdf_file/0003/345288/The-power-behind-South-East-Queensland-Form-8123.pdf

Energex. (2016). Energex disribution annual planning report 2016/17-2020/21. Energex. Retrieved October 24, 2017, from https://www.energex.com.au/__data/assets/pdf_file/0008/371519/2016-DAPR-Volume-2.pdf

Energex Planning Reports. (2017). previous distribution annaual planning reports. Retrieved from energex reports: https://www.energex.com.au/about-us/company-information/company-policies-And-reports/previous-distribution-annual-planning-reports

Ernest & Young. (2017). Cyebersecurity risks in power and utilities. EY UK. Retrieved October 23, 2017, from https://www.ey.com/gl/en/industries/power---utilities/ey-cybersecurity-risks-in-power-and-utilities-2

GHD. (2014). Infrastructure Maintenance: A report for infrastructure Australia 2124058. Infrastructure Australia. GHD. Retrieved October 23, 2017, from https://infrastructureaustralia.gov.au/policy-publications/publications/files/GHD-Infrastructure-Maintenance.pdf

Goerdin, S. A., Mehairjan, R. P., Hanea, A. M., Smit, J. J., & Van Voorden, A. M. (2015). Application of Monte Carlo Simulation to Support Riskbased Decision Making in MV Distribution Networks. CIRED 23rd International COnference on Electricity Distribution . 

Gonzalez, R. J., Fernandez, G. D., & de la Pena, C. (2016, October). How analytics can improve asset management. Retrieved from McKinsey & Company: https://www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/how-analytics-can-improve-asset-management-in-electric-power-networks

Haines, S., & Hodkiewicz, M. R. (2014). Case Study: Level of service criteria for critical rotating assets. In S. Haines, & M. R. Hodkiewicz, Engineering Asset Management 2011: Lecture notes in Mechanical Engineering (pp. 519-532). London: Springer.

Hill, C., Jones, G. R., & Schilling, M. A. (2014). Strategic Management: Theory: An integrated approach. Cengage.

Igor, H., Kyeong, K., & Bae, Y. C. (2012). Multple perpectives framework to model complex processes. Australasian conference on information systems ( 23rd: 2012: Geelong, Victoria). 

ISO. (2014). ISO 55000: 2014 Asset management-Overview, principles and terminology. Retrieved from iso.org: Asset Management Capability Models

Kerin, R. (2014). Electricity Distribution in Australia. IBISWorld Industry Report D2630. Retrieved from https://www.aer.gov.au/system/files/F7%20-%20IBIS%20World%2C%20IBIS%20World%20Industry%20report%20D2630%2C%20Electricity%20Distribution%20in%20Australia.pdf

Kerry, B., & Robyn, K. (2015). Asset Management Capability Maturity Model. Asset Institute. Retrieved October 23, 2017, from https://www.apv.net/wp-content/uploads/2016/07/Asset-Institute-Asset-Management-Capability-Maturity-Model.pdf

Khatod, D. K., & Viral, R. (2012). Optimal planning of distributed generation systems in distribution system: A review. Renewable and Sustainable Energy Reviews, 5146-5165.

Kurien, G. P., & Qureshi, M. N. (2011). Study perfomance measurement practices in supply chain management. International Journal of Business Management and Social Sciences, 2(4), 19-34.

Kwon, O., Lee, N., & Shin, B. (2014). Data quality management, data usage experience and acquisition intention of big data analytics. International Journal of Information Management, 34(3), 387-394.

Life Cycle Excellence. (2016). LCE's asset management system implimentation framework. Retrieved from Life Cycle Excellence: https://www.lce.com/Asset-Management-Systems-and-Capabilities-1766.html

Lin, M. (2007). Condition monitoring in engineering asset management. Asia Pacific Vibration Conference ( APVC) (pp. 1-16). Sapporo, Japan: APVC.

Mezger, F. (2014). Toward a capability based conceptualization of business model innovation: Insights from an explorative study. R & D Management, 429-449.

News, A. (2016). Fact Check, Does privatization increase electricity bills. ABC News. Retrieved October 23, 2017, from https://www.abc.net.au/news/factcheck/2015-03-25/fact-check-does-privatisation-increase-electricity-prices3f/6329316

Oshiro, F. (2017, August 24). Reliability and maintenance data improvement based on ISO 14224. Retrieved from Maintenance online: https://www.maintenanceonline.co.uk/article.asp?id=11644

Pearlson, K. E., Saunders, C. S., & Galletta, D. F. (2016). Managing and Using Information Systems, Biinder Ready Version: A Strategic Approach. JOhn Wiley & Sons.

Peppard, J., & Ward, J. (2016). The strategic management of information systems: building a digital strategy. John Wiley & Sons.

Porter, L., & Tanner, S. (2012). Assessing business excellence. Routledge.

PWC. (2011). Financial reporting in the power and utilities industries. International Financial Reporting Standards. Retrieved October 23, 2017, from https://www.pwc.com/id/en/publications/assets/utilities-ifrs.pdf

Quezada, G., Szatow, A., & Liley, B. (2012). New light on an old problem; Reflcetions on barriers and enablers of distributed energy. Energy policy, 1-5.

Reichert, M., & Weber, B. (2012). Enabling flexibility in process-aware information systems: Challenges, methods, technologies. Springer Science & Business Media.

Rummler, G. A., & Brache, A. P. (2012). Improving perfomance: How to manage the white space on the organization chart. John Wiley & Sons.

Shin, J., & Jun, H. (2015). On condition based maintenance policy. Journal of Computational Design and Egineering, 2(2), 119-127.

Siano, P. (2014, February 28). Demand response and smart grids-A survey. Renewable and sustainable energy reviews, 30, 461-478.

Simon, A., Karapetrovic, S., & Casadesus, M. (2012). Difficulties and the benefits of integrated management systems. Industrial Management & Data Systems, 112(5), 828-846.

Stirna, J., Grabis, J., Henkel, M., & Zdravkovic, J. (2012). Capability driven development-an approach to support evolving organizations. IFIP Working Conference on the Practice of Enterprise Modeling (pp. 117-131). Berlin Hieldelberg: Springer.

Subashini, S., & Kavitha, V. (2011). A survey on security issues in service delivery models of cloud computing. Journal of Network and Computer Application, 1-11.

Suwnansri, T. (2014). Asset management of power trasformer: Optimization of operation and maintenance costs. Electrical Engineering Congress. Chonburi, Thailand: IEEE .

Svenska. (2014). Drivers and barriers for a transition to a sustainable energy system. Till Vaxt Analysis. Retrieved July 15, 2017, from https://www.tillvaxtanalys.se/in-english/publications/pm/pm-working-paper/2014-07-15-drivers-and-barriers-for-a-transition-to-a-sustainable-energy-system-----an-analysis-of-the-electricity-market.html

Symphony Summit. (2017). Summit Asset Management. Retrieved from Symphonysummit: https://symphonysummit.com/products/summit-asset-management

Teece, D. J. (2012). Dynamic capabilities: Routines versus entrepreneurial action. Journal of Management Studies, 49(8), 1395-1401.

The Asset Management Council. (2017). Retrieved from Engineer Australia: https://www.engineersaustralia.org.au/Communities-And-Groups/Technical-Societies/Asset-Management-Council

Wang, M., Vandermaar, A. J., & Srivastava. (2002). Review of condition assessment of power transformers in service. IEEE Electr Institution Mag, 12-25.

Zhu, Q., Sarkis, J., & Lai, K. H. (2012). Examining the effects of green supply chain management practices and their mediations on perfomance improvements. International Journal of Production Research, 50(5), 1377-1394.