Computerized Crane Selection for Construction Projects (original) (raw)
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D-CRANE: a database system for utilization of cranes
Canadian Journal of Civil Engineering, 2000
Crane selection is a time consuming process that involves extensive data manipulation. Several systems have been developed to assist in selecting cranes and in planning their lifts. These systems lack the support of a comprehensive database to provide information about crane configurations, their lift capacity settings, and rigging equipment. Although crane manufacturers provide data for their cranes, these data are not always consistent and do not follow a standard format. This creates frequent problems for crane users, especially when interpolating the load charts. This requires the users to make decisions based on job conditions and categories of cranes, which can lead to costly mistakes. This paper describes the development of a comprehensive database (called D-CRANE) designed to support efficient selection of cranes. D-CRANE has been developed in collaboration with an industrial partner. It includes operational information about crane geometry, lift configurations, lift capacity settings, accessories, and attachments. D-CRANE has a number of interesting features: (i) powerful graphics capabilities, featuring a multimedia environment and a practical user-friendly interface; (ii) capacity to accommodate different types of commercially available cranes; (iii) powerful storage, sorting, and query routines; (iv) flexibility in using metric and empirical units; (v) capability of operating in a network environment, and (vi) minimum disk storage space. D-CRANE is a relational database designed using entity relation diagram and is implemented using MS-Access database management system. A case example is presented to demonstrate the use and capabilities of D-CRANE.
An Integrated Approach to the Development of Construction Site Crane Operations
Proceedings of the 5th International Symposium on Automation and Robotics in Construction (ISARC)
The following is a review of the current status and future plans of the research concerning tower crane operations, carried out by the Technical Research Centre of Finland (VTT). Firstly, an empirical time-motion study of crane operations on building sites is described. The results can be used for creating a crane selection guideline in a textual or knowledge based form and in crane automation ideas evaluation. Secondly, the current crane automation research results carried out by VTT are summarized and possible applications to a tower crane are characterized. Thirdly, some of the future activities in crane automation research in VTT are discussed. In those studies an integrated approach to crane automation problems will be applied, where development of the site's overall order, systematic construction management methods, knowledge or simulation based crane selection methods, adaptation of building components and crane automation will be gradually combined on the way to the long term goal: a highly automated building frame erection system.
A software prototype for material handling equipment selection for construction sites
Nowadays, every industry is experiencing demographic, economic and technological shifts, which have made innovation indispensable for them. The innovation in the construction industry can be evidenced through availability of a diverse range of new material handling equipments (MHEs) in the market having varying advanced features. AnMHE is a critical investmentmade by a construction company thatmay significantly affect its future performance, competitiveness and sustainability. Therefore, selecting the bestMHE with the desirable characteristics from a vast array of available alternatives is one of the most onerous tasks as often being faced by the construction engineers. In this paper, a software prototype based on quality function deployment (QFD) technique is designed and developed in Visual BASIC 6.0 for selecting two most suitable bulk-type MHEs, i.e. excavator and wheel loader for specific applications at a construction site. It is integrated with QFD method to provide due importance to the spoken and unspoken needs of the customers/construction engineers. It automates the entire MHE selection process and also performs sensitivity analysis study to investigate the effect of changing criterion weight on the alternative MHEs' ranking pattern. Its potentiality and applicability in solving bulk-type MHE selection problems is demonstrated in detail.
Intelligent computer-automated crane design using an online crane prototyping tool
In an accompanying paper submitted concurrently to this conference, we present our first complete version of a generic and modular software framework for intelligent computer-automated product design. The framework has been implemented with a client-server software architecture that automates the design of offshore cranes. The framework was demonstrated by means of a case study where we used a genetic algorithm (GA) to optimise the crane design of a real and delivered knuckleboom crane. For the chosen objective function, the optimised crane design outperformed the real crane. In this paper, we augment our aforementioned case study by implementing a new crane optimisation client in Matlab that uses a GA both for optimising a set of objective functions and for multi-objective optimisation. Communicating with an online crane prototyping tool, the optimisation client and its GA are able to optimise crane designs with respect to two selected design criteria: the maximum safe working load and the total crane weight. Our work demonstrates the modularity of the software framework as well as the viability of our approach for intelligent computer-automated design, whilst the results are valuable for informing future directions of our research.
A knowledge-based decision support system for construction project management
1995
The problem of bidding on a customized product in a manufacturing environment is very complex. Such a bidding requires determination of labor, material, production process requirements, outsourcing strategies, if necessary, and the recognition of profit margins. The complexity may arise from deciding production process requirements, which may involve hundreds of steps, selection of appropriate raw materials, and computation of profit margins in the presence of various estimates. This process is expert intensive and time consuming. The purpose of this paper is to develop a knowledge based decision support system to deal with bidding problem for a forging and steel company. The decision support system captures engineers' expertise, uses group technology principles for product classification, and uses the business domain specific knowledge. It is implemented in Microsoft Access, a relational database system. The objectives of this decision support system were to cost majority of the jobs efficiently and effectively, standardize the bidding process, aid the salespersons, and provide means to facilitate learning from past successful and unsuccessful bids. This decision support system with few modifications can be used in a variety of manufacturing and service job order environments.
A fuzzy logic approach to the selection of cranes
Automation in Construction, 1999
This paper presents a fuzzy logic approach to select the best crane type in a construction project from the main crane types, namely, mobile, tower and derrick cranes. Each factor of the project is classified as being dynamic or static according to whether the factor does or does not depend on the particular project. Linguistic information about the suitability of each Ž. crane type with respect to each factor of the project is translated into either fuzzy sets for static factors or fuzzy if-then Ž. rules for dynamic factors. The fuzzy rules are then aggregated into a fuzzy relation between the space of factor property and the space of crane efficiency. In a particular project the experts describe the property as well as the relative importance of each factor. The rules are then fired using the max-min extension principle, and the resulting efficiencies are aggregated with their importance weights. The process identifies the best crane as the one with the highest expected overall efficiency.
A Knowledge-Based System for Planning a Construction Operation
Computer-Aided Civil and Infrastructure Engineering, 2008
nowledge-based systems can be developed K as an educational tool for inexperienced construction managers and students. Microcomputer expert-system shell programs can allow knowledgebased systems to be developed and used on the construction site. Construction experts can provide knowledge which can define the best crew size, expected productivity, and the effects of production bottlenecks. This information can be incorporated in a knowledge-base and used as an aid in determining when production problems are occurring in the field. This information can also be used in the pre-construction period by providing managers and estimators with expert knowledge of expected productivity and required crew size. A prototype expert system was developed for the construction of precast concrete structures. The rules were obtained from construction experts with extensive experience in this type of construction. The system provided advice concerning the best crew size to use based upon the construction site characteristics. The system also provided advice concerning expected productivity and the effects of production problems on productivity. The prototype model was developed using the INSIGHT 2 microcomputer expert-system shell program.
Intellicrances – A Neural Network-Based Crane Selection System
1999
This database contains a senes of examples of past crane type selections. Data for each of the examples includes the type of use of the selected crane, the duration on site, the construction height, the spaciousness of the site, the site's soil bearing capacity, the physical properties of the construction, the frequency of relocations on site, site access, as well as the type of crane selected. The data is used to train and test the neural network for crane type selection. Advanced users could expand this training data to train other neural networks to maintain the Type PARAMETER Type of Use Duration on Site Construction Height
Buildings
Predictive analytics have been used to improve efficiency and productivity in the construction industry by leveraging the insights from historical data with a variety of applications in project management. In the planning process of heavy industrial construction projects, mobile crane selection plays a critical role in the project’s success, and poor choice of mobile crane configurations can lead to unnecessary cost-overrun and delayed schedules. In this research, the authors propose a predictive analytics framework for crane configuration selection using combined heuristic search and artificial neural network (ANN) approaches for heavy industrial construction projects. The heuristic search allows the practitioners to select the crane configurations based on engineering rules, while the ANN model utilizes the historical project data to help select crane configurations. The K-fold cross-validation is conducted to validate the designed ANN model and improve the accuracy of predictions...
Selection of Construction Methods: A Knowledge-Based Approach
The Scientific World Journal, 2013
The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method’ selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion,...