Capability Plot Research Articles

The Concept of Determining a Ship’s Route Based on the Capability Plot and Dijkstra’s Algorithm—Finding the Ship’s Route Between Anchorages

Determining the route from the starting point to the destination is one of the first tasks performed when planning a ship’s voyage. Before the computer age, routes were plotted manually by seafarers based on maps. Nowadays, algorithms are used for this purpose, which make it possible to reach any port in the world. In scientific publications, one can mostly find algorithms that generate global routes based on historical weather and traffic data on major sea lanes. Such routes do not take into account the current hydrometeorological conditions in the area where the ship is currently located, so that disturbances generated by environmental forces can increase energy consumption. A solution to the problem can be local routing based on the currently prevailing hydrometeorological conditions. With this approach, it is possible to respond to dynamically changing sea conditions, determine the route along which the impact of environmental forces on the hull will be least severe and minimize fuel and energy consumption. This paper presents an algorithm that determines the local passage route of an offshore ship using the example of a vessel moving to an anchorage to drop anchor. The algorithm defines a grid of points between the start point (the vessel’s current position) and the end point (the anchor position), and then determines the transition weights between each grid point based on the vessel’s capability plots. Finally, a modified Dijkstra algorithm determines the route where the sum of the transition weights will be as small as possible. During the tests, it was found that the time needed to find the passage route depended on the chosen grid density of the waypoints and was as follows: for a 6 × 6 grid—0.05 s, for an 11 × 11 grid—0.36 s, for a 16 × 16 grid—0.47 s and for a 21 × 21 grid—0.85 s. It was also found that the algorithm identified a route where the impact of environmental forces on the ship’s hull was 13% less than the direct route to the destination, resulting in a 7.5% reduction in energy consumption. The operation of the algorithm for determining the passage route was demonstrated in the anchor design tool developed in the Unity3D environment.

A method for early-stage design current loads determination on drill-ships

The increasing demand for offshore operations in deep water implies the necessity to predict station-keeping ability of offshore vessels since the early stages of design. To this end, besides developing sufficiently fast and accurate methodologies for the equilibrium resolution of the forces acting on the ship, it is of utmost importance to estimate, in a reliable way, the external forces acting on the vessel. This work focuses on the current loads, aiming at developing a model for fast current load prediction based on high-fidelity Computational Fluid Dynamics (CFD) computations. Selecting the drill-ships as reference vessel-type for the study, starting from the actual fleet operating worldwide, a systematic series of hulls has been generated varying the main hull-form parameters inside the database, according to a Box-Behnken scheme. CFD calculations based on RANS equations have been performed on the whole ship set, for a set of incidence angle varying from 0 to 180 degrees considering the hull symmetric. As numerical analyses are not suitable for fast calculations the results on the systematic series have been used as input for developing a surrogate model based on Multiple Linear Regressions (MLR). The method allows for scaling the results as a function of the Reynolds number, allowing for general and flexible applicability among different vessel dimensions. The results obtained with the developed model are compared with the conventional current loads estimation methods, and the obtained results are compared on the capability plot, highlighting the higher reliability of the proposed model for early-stage predictions.

A probabilistic approach for Dynamic Positioning capability and operability predictions

Determining Dynamic Positioning capability for an offshore vessel is mandatory to identify the environmental forces the system can counteract, together with the operability in a specific operational area of interest. Conventional predictions evaluate the capability as a maximum sustainable wind speed at a predefined encounter angle for a given wind–wave correlation, not reflecting the effective wind and waves occurrence at the site. In this respect, a step forward is provided by the scatter diagram approach, allowing the evaluation of operability in a specific sea area, using a simplified method to predict wind speed from wave parameters. Here, using known wind–waves joint distributions for the long-term environmental conditions further improves the scatter diagram approach, assessing the operability of a Dynamic Positioning system through a Quasi-Monte Carlo sampling of the joint distribution. Analysing the results of the Quasi-Monte Carlo process, it is possible to obtain a site-specific capability plot, allowing the identification of critical wind speeds in a way that is familiar to operators in the offshore industry. The application of this novel method in the case of quasi-static calculations both to a reference supply vessel and a pipe-lay vessel shows the flexibility of the proposed approach for site-specific Dynamic Positioning capability predictions.

Fast procedure for vulnerability simulation of armored vehicles

The presented work discusses performing a V/L (Vulnerability/Lethality) analysis on an armored tank based on an RHA (Rolled Aomogeneous Armour) equivalence. It is shown how the approach works using small examples verified with hand calculations. Other more complex examples include a set of welded plates protecting a HYBRID III 50 Percentile Male ATD (Anthropomorphic Test Device). Considered response parameters are the VAA (Vulnerable Area Assessment) damage maps, expected protection capability plot, and damage area fractions. Furthermore, different V/L analyses of the Russian T-80 tank are displayed. It is illustrated how to apply the concept of explicit finite element models to find the critical RHA equivalent armor thickness at normal impact. It is done with terminal ballistic models for three materials: RHA, Aluminum 5083-H116, and Armox 500T.

Dynamic positioning analysis and comfort assessment for the early design stage of large yachts

In some specific environmentally protected areas, conventional mooring systems cannot be used by large yachts for stationing at anchor and therefore, the adoption of a dynamic positioning system is required. It becomes then necessary to evaluate the station keeping capabilities of a yacht since the early-design stage. Adopting a quasi-static approach, it is possible to perform a standard capability analysis, as commonly done for the offshore industry, obtaining a capability plot as output. However, capability plots are referring to specific wind-wave correlation that are not covering all the possible wave combinations present in a sea area. Here, it is proposed to use a scatter diagram approach for the dynamic positioning analysis of a large yacht, considering the specific sea areas where the yacht shall operate, in order to figure out the downtime period of the DP system per each sea area. The proposed method can be coupled with traditional ship motions analysis, leading to a combination between comfort assessment and DP predictions. In the present work, use has been made of a traditional displacement yacht 72 m long, comparing five different DP system configurations and evaluating an enhanced comfort ranking combining ISO AWI-22834 guidelines for large yachts with ISO AWI-22822 DP analysis.

A Comparative Analysis of Energy Consumption by Conventional and Anchor Based Dynamic Positioning of Ship

One of the requirements for ships equipped with dynamic positioning system is the ability to maintain a given position in various hydrometeorological conditions. At the same time, efforts at reducing electricity consumption are made in order to reduce operating costs and emissions of exhaust gases, such as sulfur oxides and greenhouse gases such as carbon dioxide (CO2). For this purpose, the ship designer at the design stage must predict both how much energy the ship will theoretically use during operation and how the expenditure can be reduced. The publication presents a comparison of energy consumption with two different approaches to ship positioning: the use of classic dynamic positioning utilizing a set of thrusters and by using a set of anchors. In order to determine the energy consumption during positioning, the matrix method was used, on the basis of which the analysis of the ability to hold the position of the ship (capability plot) was performed, in accordance with the recommendations of the classification society DNV GL. Thanks to this analysis, it was possible to find such a distribution of thrust vectors on propulsors that the ship would not lose its set position under the hydrometeorological conditions specified in the analysis. As a result of comparing the two positioning systems, it turned out that using anchor-based positioning uses 24% less energy than positioning based on a set of thrusters, which translates into 24% less CO2 emissions into the atmosphere.

EVALUATING CRITERIA FOR DP VESSELS

The paper presents the evaluating criteria for DP vessels. A few persons tried to give a simple tool for comparing the station keeping capability between different ships. It was started in the seventies when most vessels claiming to have a DP system would be carried away by the current only (the limit was 1.5 up to 2 knots). Mainly DNV and ABS, next IMO prepared the calculating methods for DP system evaluation during the design process to receive the DP class 1, 2 or 3. The regulations may help but it’s still only rough estimate. One of them is the most popular. It is the capability plot presenting at preliminary the polar diagram with number envelops, showing the vessel’s capability to keep position or heading with a certain combination of thrusters in operation. The number, type, total power (or thrust) and location of thrusters are vital for estimating the DP capability from the propulsion system. The other equipment is only accessories assisting the DP system. At the end the sea trial may check and confirm the DP class of the vessel. The real capability for station keeping will be verified during normal operation, essentially during emergency situations like electric network faults, propulsion system failure up to damages and fire. It is needed some indexes or parameters during the design process to avoid serious faults. The paper is a probe of becoming familiar with chosen criteria.

Fuzzy process capability plots for families of one-sided specification limits

Process capability indices (PCIs) have been popularly used in the manufacturing industry for measuring process potential and performance. When our data are imprecise, classical PCIs are improper. In this paper, a graphical approach has been presented for monitoring whether or not our process is capable by using the process capability plots for two families of the one-sided PCIs based on fuzzy data. The presented methodology takes into consideration the certain degree of imprecision on the sample data and leads to the three-decision rule that has been presented on the process capability plot. Also, the advantages of this method in comparison to the fuzzy hypothesis test have been discussed. Two real examples have been presented to demonstrate this approach.

Elliptical safety region plots for C pk

The process capability index C pk is widely used when measuring the capability of a manufacturing process. A process is defined to be capable if the capability index exceeds a stated threshold value, e.g. C pk >4/3. This inequality can be expressed graphically using a process capability plot, which is a plot in the plane defined by the process mean and the process standard deviation, showing the region for a capable process. In the process capability plot, a safety region can be plotted to obtain a simple graphical decision rule to assess process capability at a given significance level. We consider safety regions to be used for the index C pk . Under the assumption of normality, we derive elliptical safety regions so that, using a random sample, conclusions about the process capability can be drawn at a given significance level. This simple graphical tool is helpful when trying to understand whether it is the variability, the deviation from target, or both that need to be reduced to improve the capability. Furthermore, using safety regions, several characteristics with different specification limits and different sample sizes can be monitored in the same plot. The proposed graphical decision rule is also investigated with respect to power.

Multi-process capability plot and fuzzy inference evaluation

Process capability indices C p, C pk, C pm and C pp fitting for nominal-the-best type quality characteristics, are effective tools to assess process capability since these indices can reflect a centering process capability and process yield adequately. The index C pp introduced by Greenwith and Jahr-Schaffrath [Greenwith, M., Jahr-Schaffrath, B.L., 1995. A process incapability index. International Journal of Quality and Reliability Management 12, 58–71] provides additional and individual information concerning the process accuracy and the process precision. Although C pp is useful to evaluate process capability for a single product in common situation, C pp cannot be applied to evaluate the multi-process capability. Referring to Vännman and Deleryd's ( C dr, C dp)-plot, a fuzzy inference approach is proposed in our study to evaluate the multi-process capability based on distance values of a confidence box. This method takes the advantages of fuzzy systems such that a grade instead of sharp evaluation result can be obtained. An illustrated example of color STN display demonstrates that the presented method is effective for assessment of multi-process capability.

Process capability plots—a quality improvement tool

We introduce the concept of process capability plots, which are powerful tools to monitor and improve the capability of industrial processes. An advantage of using a process capability plot, compared with using a traditional process capability index alone, when deciding whether a process can be considered capable or not, is that we will instantly get information about the location and spread of the studied characteristic. When the process is non-capable, the plots are helpful when trying to understand if it is the variability, the deviation from target or both that need to be reduced to improve the capability. In this way the proposed graphical methods give a clear direction of quality improvement. We evaluate two different process capability plots, the (δ*, γ*)-plot and the confidence rectangle plot, from a theoretical as well as a practical point of view. When studying them from a theoretical point of view, among other things, a simulation study is conducted to investigate the ability of each of the two methods to identify that a process is capable when it actually is. The comparison from a practical point of view is made by discussing the advantages and disadvantages of the two methods in different practical situations. Based on the above-mentioned comparisons, the recommendation is that the practitioner should use the (δ*, γ*)-plot. Copyright © 1999 John Wiley & Sons, Ltd.

IMPLEMENTING THE CIRCLE TECHNIQUE USING SPREADSHEETS

Click to increase image sizeClick to decrease image sizekey words: Circle techniqueCapability plotChi-squared distributionShewhart chartsProcess control

Assessment and comparison of multivariate process capability indices in ceramic industry

Process capability indices are intended to provide a single-number assessment of the consistency of a manufacturing process relative to the engineering specification limits on quality characteristics. In many industrial instances product quality depends on a multitude of dependent characteristics and as a consequence, attention on capability indices shifts from univariate domain to multivariate domain. In this paper five different multivariate methodologies are used for measuring and comparing capability of a ceramic table-ware manufacturing process. Based on their multivariate process capability index values and expected rejection rate, the result shows that Castagliola's index is the best and followed by Chen, Taam, Shahriari and Braun respectively in this case. Keywords: Process capability indices, Multivariate process capability indices, Multivariate Capability Plot, Multivariate control chart doi:10.3329/jme.v39i1.1829 Journal of Mechanical Engineering, vol. ME39, No. 1, June 2008 18-25