An optimal maintenance plan for building envelope insulation materials after retrofitting

ABSTRACTPT Bank Danamon Indonesia, is one of the banks affected by the development of information technology and is the bank with the most employees shrinking among ten medium and large scale banks in Indonesia from 2015-2018. Along with the number of employee depreciation that occurred, the company's revenue and net profit actually increased. This research aims to find out the feasibility of IT/SI investments made in PT Bank Danamon Indonesia. The analysis was carried out using Cost Benefit Analysis calculations including Return On Invesment (ROI), Payback Period (PP), Net Present Value (NVP) and Benefit Cost Ratio (BCR). With a Return on Invesment yield of 1.32%, Payback Period of 0.43, Net Present Value of Rp. 18,826,196, and Benefit Cost Ratio of 9.21 which indicates that the investment has a good profitability with a return time of less than one year.Keywords: information technology investment, Cost Benefit Analysis, Return On Invesment, Payback Period, Net Present Value, Benefit Cost Ratio.ABSTRAKPT Bank Danamon Indonesia , merupakan salah satu bank yang terkena dampak dari perkembangan teknologi informasi dan merupakan bank dengan penyusutan jumlah karyawan paling banyak diantara sepuluh bank dengan skala menengah dan besar di Indonesia dari tahun 2015-2018. Bersamaan dengan jumlah penyusutan karyawan yang terjadi, pendapatan dan laba bersih perusahaan justru mengalami kenaikan. Penelitian ini bertujuan untuk mengetahui kelayakan dari investasi TI/SI yang dilakukan pada PT Bank Danamon Indonesia. Analisis dilakukan dengan menggunakan perhitungan Cost Benefit Analysis diantaranya Return On Invesment (ROI), Payback Period (PP), Net Present Value (NVP) dan Benefit Cost Ratio (BCR). Dengan hasil Return on Invesment sebesar 1.32%, Payback Period sebanyak 0.43, Net Present Value sebanyak Rp. 18.826.196 , dan Benefit Cost Ratio sebanyak 9.21 yang menandakan investasi memiliki profitabilitas yang cukup baik dengan waktu pengembalian yang kurang dari satu tahun.Kata kunci: investasi teknologi informasi,Cost Benefit Analysis, Return On Invesment , Payback Period , Net Present Value, Benefit Cost Ratio.

Circular Economy, founded on the self-generative economic system concept, can be traced back to the Life Cycle Thinking, that conceives the project as a process along its whole life cycle, at the different scales: material, component, system, building, urban district and territorial area, infrastructure. In Italy, as in the main part of European Countries, a great portion of infrastructures was built in reinforced concrete before 1960 and is approaching the end-of-life stage. Thus, aim of this article is to propose an operative modality for supporting the preventive maintenance investments planning in function of life cycle costs and benefits, assuming the presence of uncertainty over time. Firstly, a recalling of the Cost Benefit Analysis (CBA) approach is presented. Secondly, the Life Cycle Cost Benefit Analysis (LCCBA) approach is proposed, as a tool for supporting long-term investments, management of public services and maintenance planning activities in the infrastructure sector. Thirdly, by integrating CBA and LCCBA, an operative modality is proposed. On the background, life cycle management, optimal maintenance planning and durability concepts are assumed.

A mathematical programming approach to optimize process plant performance subject to equipment failure is presented. The optimal production planning and scheduling in multipurpose process plants involves the efficient utilization of assets and resources to produce a number of products so as to satisfy market demands while optimizing a performance criterion. However, the degree of utilization of process plant components, within the time horizon of operation, critically depends on the level of equipment availability. The interactions between production and maintenance planning as well as the necessary links to quantify the strong interactions between them are studied. The preventive maintenance planning and crew allocation problem are used to demonstrate the effectiveness of the proposed approach. The overall problem is first formulated as an optimal control problem by integrating an aggregate production planning model with a continuous time Markov chain maintenance model. The resulting problem is then transformed into a mixed-integer linear programming model by using an Euler discretization scheme and appropriate linearizations of bilinear terms. Finally, extensions to include design aspects are also discussed. The applicability of the proposed approach is demonstrated by a number of illustrative examples.

In order to establish a rational bridge management program, it is necessary to develop a cost-effective decision-support system for the maintenance of bridges. In this paper, an attempt is made to develop a bridge management system that can provide practical maintenance plans by using an improved multi-objective genetic algorithm. A group of bridges is analyzed to demonstrate the applicability and efficiency of the proposed method. INTRODUCTIONIn Japan, maintenance work on bridge structures is increasing in volume and importance. The number of structures requiring repair or replacement will drastically increase in the coming ten years. In order to establish a rational maintenance program, the concept of Life-Cycle Cost (LCC) has gained great attention, which minimizes the total cost of whole lives of structures [1]. So far, the authors have developed LCC based bridge maintenance systems for existing concrete bridge structures [2, 3]. Concrete bridges are deteriorating due to the corrosion of reinforcing bars and the neutralization of concrete. Then, it is necessary to achieve an optimal maintenance plan that can provide appropriate methods and times of repair or replacement. However, the optimal maintenance problem is very difficult to solve, because it is one of combinatorial problems with discrete design variables and discontinuous objective functions. Furthermore, the tougher problem becomes , the larger and more complex it is. Although low-cost maintenance plans are desirable for bridge owners it is necessary to consider lifetime constraints when choosing an appropriate maintenance program. For example, the minimization of maintenance cost needs the target safety level and the expected service lifetime to be both prescribed. The predetermination of requirements may affect the possible maintenance plans. Namely, it may be possible to find out a better solution that can largely extend the service life if the safety level can be slightly decreased using the same amount of maintenance cost [4, 5]. In this paper, an attempt is made to improve the bridge management system proposed in [6], by developing an improved multi-objective genetic algorithm. Many alternative 17 ANALYSIS AND COMPUTATION SPECIALTY CONFERENCE th Copyright ASCE 2006 17th Analysis and Computation Conference maintenance plans with different characteristics can be obtained by introducing the concept of multi-objective optimization. Single-objective optimization can provide various solutions by changing the constraints. However, this approach requires enormous computation time. When selecting a practical maintenance plan, it is essential to compare feasible solutions obtained under various conditions. This process is effective for the accountability through the disclosure of information. A new multi-objective genetic algorithm is developed for the bridge management problems that have a lot of constraints. Several numerical examples are presented to demonstrate the applicability and efficiency of the proposed method.

A general procedure for highway maintenance planning at the project level is developed in this study. Three key models used in the planning process are explored as well; the performance prediction model, the thickness equivalent model and the cost-benefit analysis model. The process of maintenance planning can be divided into six steps and the maintenance plan optimization is based on Life Cycle Cost Analysis (LCCA). This study examines a real asphalt highway in Northern China to explain in detail how to develop project-level planning. The planning results include both maintenance strategies and maintenance time. According to the feedback from the field research, the maintenance plan made by this way is in agreement with the local working experience and quantifies the experience.

Integrity tests, inspections (caliper log) and maintenance activities are critical to the integrity management of the production tubing and are important to ensure that loss of production — due to e.g. excessive reduction in the wells cross-section and numerous unplanned shut-ins, is reduced over the service life while maintaining safety and availability. The progressive loss of integrity of production resulting from deterioration processes such as scaling, are time variant with large uncertainties. The time variability together with large uncertainties is one main driver of increasing need of rational tools for cost-optimal planning of inspections and maintenance. Optimal planning of inspections and maintenance is therefore necessary to achieve timely and risk-efficient management of the production wells by finding a trade-off between the cost of inspection and maintenance, and the benefit of increased production amongst others. This paper presents a framework for identifying cost-optimal planning of inspections and maintenance of the production tubing of sub-surface oil and gas wells subject to time dependent scale degradation. The proposed framework is based on a risk-based approach, which allows uncertainties to be accounted for. By adopting this approach, the strategies which give the minimum expected value of the total cost of inspection and maintenance are identified. In this paper, the approach uses categorization of the sizes of scale thickness characterized by damage sizes, and inspection results into damage states, and takes into account imperfection in the inspection results in terms of the probability of detection and damage sizing accuracy. For each of the damage states, a certain damage cost and maintenance decision rules, stating the next line of action, are established. The inspection and maintenance decision problems are therefore modeled based on the pre-defined decision rules while the optimization parameters are the intervals of inspections and the maintenance alternatives. The probabilistic model, accounting for uncertainties, scale propagation proposed by Guan et. al. (2019) is used to describe the scale growth or damage evolution. Bayesian pre-posterior decision theory is the basis for the decision making. All costs — including damage, inspections and maintenance costs, through the lifetime of the production tubing are evaluated and included in the decision model and the expected value of the life cycle costs are estimated and compared for different maintenance alternatives. An example in the paper demonstrates the framework and the implementation of the decision rules for one sub-surface production well subject to calcite scales.

Cost-effective bridge maintenance planning requires balanced consideration of long-term bridge performance and life-cycle maintenance cost. Many of the existing methodologies determine an optimal maintenance planning solution based solely on life-cycle cost minimization while enforcing constraints on bridge performance. The resulting single planning solution, however, may not always satisfy bridge managers' specific requirements for bridge performance over an intended time horizon. In response, the life-cycle maintenance planning of deteriorating bridges is formulated as a multiobjective optimization problem and is solved by a genetic algorithm. The visual inspection-based condition state, structural assessment-based safety state, and cumulative life-cycle maintenance cost are all treated as competing criteria. A group of different maintenance strategies is considered. A multilinear computational model is adopted to predict time-varying deterioration processes under no-maintenance and maintenance interven...

The medium and long-term operation of the unit is an important part of the operation of the power energy system. With the development of IES, the coupling of various energy forms such as electricity, heat and natural gas has been continuously strengthened. When a CHP unit or a gas unit is shut down, its impact will involve a variety of energy systems. Therefore, It is of great significance to formulate a reasonable annual unit combination plan and a coordinated optimization plan for the maintenance plan. First of all, starting from the coupling mechanism of the power supply, heating and gas supply of the unit, consider the relationship between each system and equipment. On this basis, taking into account the system operation constraints, unit maintenance constraints and unit operation constraints, a combined dispatch model of IES unit combination and maintenance plan including power-to-gas (P2G) and electric boiler equipment are proposed. The accuracy and effectiveness of the proposed model are verified through simulation analysis of a numerical example. The calculation example results show that the overall arrangement of the unit maintenance plan and the unit combination plan in the integrated energy system can improve the operating economy of the system; the introduction of coupling equipment such as P2G and electric boilers can effectively improve the new energy consumption rate and reduce the system operating cost.

Accurately predicting the optimal timing for preventive maintenance of road pavements aids road management and maintenance departments in developing effective maintenance plans and guiding the actual work on port collection and distribution roads. In this study, we propose an optimal preventive maintenance timing model based on benefit and emissions indicators. For benefits, a pavement performance degradation model for port roads is established by comparing and contrasting an optimized cosine function model, an exponential model, a linear model, and a logarithmic model. Regarding carbon dioxide emissions, the composition of emissions during the operation and maintenance phases is analyzed and defined. The emissions factor and quota methods are used to quantify carbon emissions and establish the emissions model. Finally, using port collection and distribution roads as the research subject, we constructed a multi-objective decision-making function aimed at maximizing benefits and minimizing carbon dioxide emissions. The eligible Pareto solution set was solved using MATLAB to optimize the timing of preventive maintenance. The optimal maintenance plan was then determined through marginal effect analysis, validating the feasibility and rationality of the proposed model.

Optimal inspections and maintenance planning for anti-corrosion coating failure on ships using non-homogeneous Poisson Processes

Integrated condition-based track maintenance planning and crew scheduling of railway networks

With the increase of high-speed emu operation mileage, the complexity and the cost to maintenance the emu is also increasing, so a scientific and comprehensive maintenance plan model for reducing excessive repair and improving maintenance efficiency is of great importance. A comprehensive analysis of the establishment of the emu maintenance plan needs to consider such factors as the mileage of the emu vehicles in service, the maintenance capacity of the base, the peak of passenger flow in holidays, and the maintenance of the normal transportation capacity of the road bureau, we propose to use these parameters such as the remaining mileage, whether more than maintenance ability and the number of hot standby as the evaluation index of the emu advanced maintenance plan model. And by using the particle swarm optimization (PSO) algorithm solving process control, advanced maintenance plan model parameter tuning, strong ability of global optimization can be obtained, thus obtains the optimal base maintenance plan, to achieve the purpose of enhance maintenance efficiency.

In this work, we develop methods to assess the risk of profit–loss resulting from the choice of a computational method for solving a joint production and maintenance-planning problem. In fact, the optimal objective function is calculated via the use of algorithms and optimization methods. The use of these methods can have an impact on an event that can disrupt the optimal production and maintenance plan. To achieve our goals, we start with calculating the manufacturing system’s joint production and maintenance plans over a finite horizon using different methods. In the second part of the work, we propose analytical models to quantify the risk of profit–loss resulting from product returns and the integration of an imperfect maintenance policy. Numerical examples are conducted by adopting the different algorithms used. This study provides insights into the most efficient computational methods for the encountered problems. This research proposes new approaches to help and guide managers in the analysis and evaluation of their decisions.

PurposeThe aim of this research is to carry out a literature review of the use of life cycle costing (LCC) in the urban agriculture (UA) sector by analysing its evolution over a 22-year period from its beginning in 1996 to July 2018.MethodsA total of 442 references were obtained from two principal databases, Scopus and Web of Science (WoS). After a long refining process, 20 (4.5%) references containing the keywords LCC and UA were selected for analysis. Then, we classified and organized the selected references in 4 groups. Qualitative methods were used for analysis, and results on general characteristics of the 20 references and by each group were elaborated. Lastly, we discussed and concluded the most significant findings. Limitations and future research were also included.Results and discussionOur major findings were as follows: (i) urban horticulture was the most studied urban agriculture practice among studies that used LCC for UA; (ii) LCC plays a secondary role in its integration with LCA; (iii) only 4 of the10 papers in group 1 used additional financial tools; (iv) very few (3) papers appropriately applied the four main LCC stages; and on the other side, essential costs like infrastructure, labour, maintenance, and end-of-life were frequently not included.ConclusionsSince we found that life cycle assessment (LCA) was the predominant methodology, we suggest that future research apply both LCA and LCC analyses at the same level. The LCC analysis was quite incomplete in terms of the costs included in each LCC stage. We recommend that the costs at the initial or construction stage be considered a necessity in future studies in order to implement these new systems on a large scale. Due to the limited use of labour cost at the operation stage, we also suggest that labour be included as an essential part of the urban production process. Finally, for more complete LCC analysis for UA, we recommend (i) that all LCC stages be considered and (ii) that additional financial tools, such as net present value (NPV), internal rate of return (IRR) and payback period (PBP), be used to complement the LCC analysis.

According to the Directorate General of EBTKE, Indonesia has a great deal of untapped potential for PLTS development because the equator passes through the country. Furthermore, the use of PLTS can mitigate the negative effects of carbon emissions caused by conventional power plants' reliance on coal. This research aims to quantify the savings in carbon emissions from PLTS deployment and to conduct an economic analysis of PLTS deployment by considering its Life Cycle Cost (LCC), Levelized Cost of Energy (LCoE), Net Present Value (NPV), and Payback Period (PBP). Profitability Index (PI) and Internal Rate of Return (IRR) for a pharmaceutical firm located in East Jakarta's PT Jakarta Industrial Estate Pulo Gadung. The results of the analysis that has been carried out obtain a total reduction in carbon emissions due to the use of PLTS when compared to JAMALI's electricity carbon emissions of 479.4 tons CO2eq in a year. The use of PLTS affects savings in paying electricity bills of IDR 591,145,354.06 each year and from the economic analysis using the methods (LCC, (LCoE), (NPV), (PBP), (IRR), and (PI) it is obtained that the feasibility The investment in PLTS development in this company is considered feasible.