Software om activities

The champion is someone who is responsible for the overall management of a building or system. The champion is knowledgeable of, and an advocate for, the proper design, use, operation, and maintenance of the building or system.

The champion understands the details and knows how to meet management's goals and objectives in the safest, and most cost-effective way possible. To succeed, a champion must have management support. Management support includes technical training for the champion and others, establishing and managing key performance indicators, and commitment to implementing change to increase performance.

Create a best-practice system for tracking utility information and communicate the results both vertically and laterally in the organization. Evaluate and select an energy-accounting software tool to track energy use and monitor performance goals. Some utilities offer their customers excellent free or low-cost programs with automatic data uploading.

Programs are also available from private vendors. With your permission, some private vendors can work directly with your utility to collect consumption data periodically. Energy-accounting programs have a wide variety of features and user interfaces. For instance, the ability to update utility data in a web-based program may be a desirable feature.

Carefully evaluate several programs before selecting one. If you buy from a vendor, request a trial period to thoroughly evaluate the product. When you select a system, establish responsibilities for implementation and maintenance. Broad employee access to energy-consumption data promotes awareness of energy use throughout the organization and collective ownership in reducing energy use.

Providing read-only access on your organization's intranet is highly recommended. With the energy-accounting system providing a clear picture of building-energy use, establish performance goals. Goals should be realistic and achievable based on established benchmarks.

Benchmarks create a standard for measuring building-energy performance. Energy performance benchmarks may be based on similar buildings in a portfolio or campus, or other standards such as the Environmental Protection Agency's EPA Energy Star Portfolio Manager.

This web-based program has a benchmarking feature that ranks the energy use of a building among a large database of similar buildings. When comparing buildings in your campus or portfolio, be sure to use a common metric such as energy use per square foot of conditioned space, to create an "apples-to-apples" comparison.

The perpetual question should be, "How can we be more energy efficient? Provide monthly feedback to building-operation staff on building-energy use relative to goals and benchmarks. Building-energy-performance data should be easily accessible to all employees.

Benchmarking will identify buildings with higher than normal energy use. These are the best targets for a building tune-up. If your organization has more than one building, a strategic approach is to identify one building that most needs improving, conduct the building tune-up at that building, then expand the program to build on that initial success. The outcome will include a list of low-cost modifications and the follow-up improvements and modifications. A well-executed tune-up will noticeably reduce energy consumption.

For example, the decision to purchase replacement equipment should consider long-term or life-cycle operating costs. A low-first-cost option may have costly long-term effects. Many utilities offer rebate programs to help offset the higher first cost of high-efficiency equipment. Service contracts are another area where a lowest-first-cost option may have adverse long-term effects. Consider applying for a building award or certification that signifies achieving a recognized standard of energy and environmental excellence.

These certifications are attractive to building occupants and tenants as well as the building operations' team, and will have positive effects on marketing and staff morale. There are three general approaches to maintenance management: reactive, preventive, and predictive. Most organizations use a combination of reactive and preventive maintenance with or without maintenance-service contractors. Generally, the most cost-effective solution is a combination of preventive and predictive maintenance that appropriately balances prevention and repair.

Computerized maintenance-management systems CMMS automate and streamline the logistical tasks associated with maintenance programs. CMMS capabilities include generating work orders, tracking work orders, tracking equipment performance, tracking periodic or run-hour-based preventive maintenance, and tracking outside service calls and dispatches, plus many other functions which may be desirable for a particular organization.

Overall, a CMMS will eliminate tedious paperwork, increase staff productivity, and streamline maintenance monitoring for management. While these systems go a long way toward improving the efficiency of maintenance, there are some common pitfalls in adopting them. Although no underlying articles exist yet for this topic, topic-level best practices and lessons learned are presented below. When available, the articles in this topic will describe best practices and lessons learned for transitioning a system from its acquisition phase to the remainder of its life cycle.

View transition as a process. The transition process should not be deferred until after the product is developed and ready to be produced and fielded, or the likelihood of failure is greater.

Begin planning the transition process early in the development phase to account for any uniqueness in manufacturing, fielding, or maintenance activities. Start planning for the transition early in the product development phase, even before the initial design review. Include manufacturing engineers and field-service engineers in the product planning phase to ensure that the development engineers understand how the product will be produced and maintained.

Minor changes in the design, if done early on, can provide a significant benefit to the person who must build or maintain the product. Walk the manufacturing floor. Have the SEs tour the manufacturing or integration facility and understand how a product "flows" through the plant. Figure Weather windows for the 5-day forecast 18th—22nd November Green color indicates values below threshold, red color above threshold. Night hours are in gray, day hours in cyan.

The sensitivity of the tool to uncertainties of the metocean forecast was tested in the same scenario. The scenario was thus simulated again with the modified metocean forecast, while track, speeds, operation thresholds were kept identical. As an example, working at the Site on the 19th between 16 and 17 turned to be feasible. Nevertheless, the overall weather window assessment did not differ much from the outcome shown in Figure The capability of the tool to convert metocean conditions into actual workability criteria related to vessel motions can, to some extent, reduce the potential impact of forecast errors on weather window analyses.

As mentioned in the introduction of this paper, the aim of the tool is to provide weather windows more reliable than traditional workability assessments based on metocean conditions directly. In order to investigate the degree to which the tool has such capability, the application presented in section 3 was repeated on a 6 month-hindcast dataset 1 October —31 March The workability determined by the tool was compared with the predictions of the traditional approach.

It is highlighted that the tool was set to initiate a new trip to the OWF every hour, which gave a total of 1, simulated trips during the investigated period.

Therefore, the probabilistic comparison presented in the following was based on a large metocean and vessel response dataset. The chosen hindcast period allowed to compare the assessment of the tool and the traditional approach for the winter months, during which weather windows are expected to be infrequent and trustworthy predictions of workability are thus more critical than in the summer season.

The output time series of metocean and vessel response parameters were elaborated as explained in the following. A simulated trip was assessed feasible, either by the tool or the traditional approach, if both the transfer to the OWF sail-out and the operations at the Site were feasible.

No constraints were applied on the sail-in phase. The tool applied thresholds on the Motion Sickness Incidence and the heave of the bow, i. For the traditional approach, two different thresholds were applied on the significant wave height during the transfer and during the operations at the Site, i.

A trip was thus defined successful when the following conditions occurred. Based on the conditions in Equation 12 , a success rate was defined as the number of successful trips out of the 1, trips simulated during the 6 months period.

Per each of those 81 combinations, an iterative procedure was applied to estimate a pair of thresholds H s,sail-out LIM - H s,site LIM with which the traditional approach provided the same success rate. With the known pairs of thresholds H s,sail-out LIM - H s,site LIM , the predictions of the tool and the traditional approach were compared per each simulated trip as explained in the following.

The results of this analysis are shown in Figure When MSI was not constrained, i. Results of the analysis for the hindcast 1st October —31st March The above-mentioned iterative procedure allowed to find the corresponding thresholds on the significant wave height for the traditional approach, i.

The feasibility of all trips carried out in each month was assessed with both methods and the monthly success rates were derived. Results are shown in Figure It can be observed that November was the most successful month according to both methods.

For the rest of the period, the two methods provided similar success rates. Monthly success rate over the investigated hindcast period predicted by the developed tool blue line and the traditional approach red line. As the route of the CTV was fixed throughout the whole simulated hindcast scenario, the sensitivity of the results of the tool to the chosen route was investigated. The hindcast scenario was then simulated again with changing the CTV route only, to potentially increase or decrease the impact of MSI in the long-term.

With the modified route, the vessel sailed first westerly and then northerly to reach the Site. It is worth mentioning the computational demand of the developed tool. The simulation of the 5-day forecast took 2 min on one core of a standard laptop, while 1 h was necessary for the hindcast scenario. Such low computational time-demand is an important dimension in both forecast and hindcast scenarios and it is primarily due to the use of an ABM framework for modeling.

This characteristic allows fast re-execution of the tool in daily operations, when a new forecast dataset is available as an example and to run the model with ensemble input allowing a probability of success to be defined for each start time.

The main aim of the study was to show how workability predictions can be different when based instead on direct measures of workability, that is seasickness during the trip to OWF or bow displacements that make the crew transfer from vessel to turbine mono-pile difficult.

The study has shown the key capability of the tool of calculating the motions of the vessel employed in the operations. The vessel motions were used to produce two direct measures of the workable conditions, i. The paper has also shown that the tool can be used with hindcast metocean databases, hence for simulations covering several months or years. This capability supports long-term seasonal plans when it is necessary to know, as an example, what is the likelihood that a specific task can be executed in a certain month as well as for cost estimation during design.

The application in the hypothetical, but realistic, hindcast scenario enlightened the extent to which the predictions of the two methods, i. The vessel motions, the metocean conditions and the feedback of the crew about workability will be measured and compared with the predictions of the tool. Furthermore, the numerical engine will include the adaptation of the route and the speed of the vessel to local adverse metocean conditions during the simulation.

With such feature, it will be possible to flexibly minimize the impact of the weather conditions on the feasibility of the transfer to the offshore site, hence to potentially increase the availability of weather windows.

Publicly available datasets were analyzed in this study. PT was responsible for the development of the tool, the presented analyses, and for writing the draft of this paper. MD supervised the development of the tool and contributed to the presented analyses. RB assisted in the metocean data collection and reviewed the draft. JS proposed the idea of developing the presented tool and reviewed the draft.

All authors contributed to the article and approved the submitted version. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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