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Global Warming and Alternative Energy Awareness Essay

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Updated: Nov 5th, 2020


The hypothesis developed for the paper is as follows: system engineering approach is very important for any police department to establish an effective information system.

Literature Review

Research and Development

The Knowledge Cycle Model was discussed by Evans, Dalkir, and Bidian (2015) who point out that the model might be useful for storing and sharing information collected in an organization throughout the life cycle of the project. Thus, before constructing or establishing a database, the organization might use KCM to understand how to decrease the costs of all stages of production and collect all data available in the organization.

Evans, Dalkir, and Bidian (2015) name seven phases used in the KCM: identify, store, share, use, learn, improve, and create. Each of these stages is responsible for how the information is used at the development stage. Ideally, all identified information leads to the creating of new information, which is stored, then shared, then used to teach/learn, and eventually improved depending on the outcomes of learning. The advantage of the model is that “it provides a holistic view of the knowledge life cycle, by building on previous life cycles” (Evans, Dalkir & Bidian 2015, p. 95). Thus, it can be used during the research phase.

Hepperle et al. (2012) discuss the implementation of PSS (product-service-systems) based on the life cycle management model. The suggestions they make can be used for managing police database: first, its potentials can be deduced from environment and company potentials, and database-related ideas are generated with regards to those (Hepperle et al. 2012). Second, requirements for the service (database) are gathered and updated during the design process to create communication between database development and design departments. Third, service implementation can be prepared after the first two steps to finalize supporting tools (Hepperle et al. 2012).

The authors also indicate that some of the phases, as, for example, the disposal phase, cannot be finally designed before the object is launched (Hepperle et al. 2012). Therefore, it is essential for life cycle managers to consider how the design and the development of the database will affect its disposal.


Production costs of a database can be high and require efficient management. Software for database management may be developed as well during the life cycle of the project. Fricker (2012) suggests using roadmapping (planning the evolution of a product, in this case, software), release planning (requirements for release to ensure usefulness), product requirements engineering (collecting stakeholder needs, expectations, ideas) as major milestones in developing and producing software products. Myklebust (2013) provided another framework for the production of a system by suggesting the Zero Defect Manufacturing approach.

It is essential to understand that when planning a product’s lifecycle, instead of setting for future failures, companies can collect information feedback during the early phases of the product (e.g., design phase) and plant lifecycles to avoid or decrease future defects and thus reduce costs. As Myklebust (2013) points out, to reduce the number of defects that will impact cost management during the life cycle in the future, “for any activity within the product life cycle e.g. Maintenance or End of Life treatment correct product information is needed” (p. 249). Detected product defects can be stored in the life cycle databases to evaluate whether it could be avoided in the earlier phases.

Operation and Support

Operation and support cost of databases and their estimation within the boundaries of systems engineering can vary. For example, Li et al. (2012) argue that Post Deployment Software Support (PDSS) is 70% of the overall software lifecycle cost. PDSS, in turn, is divided into two major parts that need to be considered when evaluating the overall operation and support cost: Software Running Support (SRS) and Software Maintenance Support (SMS).

The former contains the daily support and problem-solving if errors occur, together with the logistics used during SRS. SMS includes the changes in the source code and the implementation of new features; these are usually carried out by a professional team. Operation and support costs will include both of these parts and vary depending on the database workload among other factors. It is important to consider uncertainty assessment as well.

When formulating the project’s initial cost estimates, unexpected events are usually regarded as unavoidable; therefore, any project cannot be entirely risk-free. The estimation of the risks itself, however, might be uncertain as well due to data inconsistencies or model limitations (Trivailo, Sippel & Şekercioğlu 2012). Wynn et al. (2013) suggest transforming Work-flow Management Systems (WfMSs) so that they can make cost-informed decisions based on cost-informed business rules, thus facilitating the overall assessment of all system lifecycle costs.

At last, an important aspect of support cost is the speed of database recovery. Various factors such as buffer replacement and checkpoints together with transaction throughput and storage media (hardware used) can either increase or decrease database recovery time, thus changing the overall support and maintenance costs (Sauer, Graefe & Härder 2014). A factor that might remain unconsidered is the influence of database workload on the choice of larger or smaller devices for it. Both of those have specific advantages and disadvantages that need to be taken into consideration due to their influence on cost management.

Retirement and Disposal

Retirement and disposal costs are normally assessed during the early phases of product or system evaluation. Sun et al. (2012) point out that the correct application of the Lifecycle Management Model can result in the extended service life of systems, which can potentially reduce their disposal costs. Verma (2016) suggests using different approaches to Life Cycle Management, e.g., algorithmic (COCOMO, Function Point) or non-algorithmic (Fuzzy, neural networks, expert judgment) methods for determining either system cost as a whole or its disposal costs.

Sakai et al. (2014) examine the disposal of end-of-life vehicles and suggest implementing various recycling programs at a governmental level as a solution to high disposal costs of systems. Thus, disposal cost varies, and each organization should consider other context-specific details when forecasting it; inaccurate forecasting will result in increased costs.

Han, Y & Liu, X 2012, ‘Adapt to transformational development promote the life cycle cost management of military supplies and equipment’, Management & Engineering, vol. 9, no. 1, pp. 7-10.


The aim of the article is to emphasize the importance of Life Cycle Cost (LCC) management of military supplies and equipment. The development of new technology has led to the growth in the costs of military equipment (Han & Liu 2012). At the same time, its functionality and total life cycle are dependent on the development process, and if any faults are present during it, its estimated duration of life decreases. Han and Liu (2012) aim to prove that the implementation of LCC can increase the reliability of military equipment.


The authors point out that the use of LCC can lead to the following improvements or implementations:

  1. The precise estimation of the expenses in advance and the introduction of the “fixed cost design” to balance the efficiency and cost of the military equipment.
  2. Making users aware that acquisition and maintenance costs should not be separated. Once the equipment is purchased, it is necessary to understand what costs its maintenance and disposal will have.
  3. An increase in the quality will result in reduced maintenance costs, thus also decreasing the reparation costs.
  4. LCC will significantly increase the equipment’s efficiency by emphasizing the importance of the development process.
  5. LCC will help conduct a thorough analysis of the optimal life cycle for military supplies and equipment and institutionalize decommissioning standards (Han & Liu 2012).

The authors believe that the use of the LCC will change the attitude toward equipment and supplies among users, improve the managerial system that exists for supervising their quality, promote legislation of this type of management, and support scientific research related to LCC (Han & Liu 2012). The decision to use LCC as the primary model can improve economic-decision making as well.


The article provides a clear explanation of how the LCC can improve the development and use of military equipment by users and make them aware of the connection between the acquisition, the maintenance, and the disposal cost. It also provides context-specific details on how LCC management is perceived in China and whether it should be applied on a greater scale to increase the quality of military supplies and equipment.

However, it does not introduce the LCC model to readers who might be unfamiliar with it in detail and therefore might be difficult to understand for those who do not know how LCC operates and is applied with regard to complex systems. At the same time, Han and Liu (2012) provide an introduction to the concept and name the stages considered in it. Thus, despite a small disadvantage, the article helps understand how LCC can change industries and organizations, as well as the quality of their products.


The article provides a detailed description of how the LCC can change the perception of acquisition and maintenance costs. However, it does not present the concept of LCC in detail. Nevertheless, it is still useful in evaluating what impact LCC can potentially have on different industries and users if applied correctly.

Reference List

Evans, M, Dalkir, K & Bidian, C 2015, ‘A holistic view of the knowledge life cycle: the knowledge management cycle (KMC) model’, The Electronic Journal of Knowledge Management, vol. 12, no. 1, pp. 85-97.

Fricker, SA 2012, ‘Software product management’, Software for People, vol. 4, no. 7, pp. 53-81.

Han, Y & Liu, X 2012, ‘Adapt to transformational development promote the life cycle cost management of military supplies and equipment’, Management & Engineering, vol. 9, no. 1, pp. 7-10.

Hepperle, C, Orawsk, R, Nolte, BD, Mörtl, M & Lindemann, U 2012, ‘An integrated lifecycle model of product-service-systems’, in Proceedings of the 2nd CIRP IPS2 conference 2010, Linköping University, Linköping, 159-166.

Li, M, Zhang, W, Lu, Q, Xia, Y & Wang, X 2012, ‘The estimated methodology for military software support cost’, in Robotics and applications (ISRA), 2012 IEEE symposium on, Seri Pacific Hotel, Kuala Lumpur, pp. 443-446.

Myklebust, O 2013, ‘Zero defect manufacturing: a product and plant oriented lifecycle approach’, Procedia CIRP, vol. 12, no. 2, pp. 246-251.

Sakai, SI, Yoshida, H, Hiratsuka, J, Vandecasteele, C, Kohlmeyer, R, Rotter, VS & Oh, GJ 2014, ‘An international comparative study of end-of-life vehicle (ELV) recycling systems’, Journal of Material Cycles and Waste Management, vol. 16, no. 1, pp. 1-20.

Sauer, C, Graefe, G & Härder, T 2014, ‘An empirical analysis of database recovery costs’, in RDSS, SIGMOD workshops, Snowbird, UT, pp. 1-6.

Sun, B, Zeng, S, Kang, R & Pecht, MG 2012, ‘Benefits and challenges of system prognostics’, IEEE Transactions on Reliability, vol. 61, no. 2, pp. 323-335.

Trivailo, O, Sippel, M & Şekercioğlu, YA 2012, ‘Review of hardware cost estimation methods, models and tools applied to early phases of space mission planning’, Progress in Aerospace Sciences, vol. 53, no. 2, pp. 1-17.

Verma, DK 2016, ‘A systematic analysis of software cost estimation techniques’, An International Refereed Journal of Commerce & Management, vol. 2, no. 1, pp. 31-51.

Wynn, MT, Reijers, HA, Adams, M, Ouyang, C, ter Hofstede, AH, van der Aalst, WM & Hoque, Z 2013, ‘Cost-informed operational process support’, in International conference on conceptual modeling, Regal Riverside Hotel, Hong Kong, pp. 174-181.

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