We have found clustering tool very useful for a ... powerful business intelligence and ... The colored bubble chart is the most powerful tool for visualization the ...
Amir Mosavi, K.N. Hewage, A.S. Milani, M.Yeheyis University of British Columbia – Okanagan, School of Engineering University of Debrecen
Grapheur 1 is a data mining, modeling and interactive visualization package implementing the Reactive Business Intelligence approach which connects the user to the software through automated and intelligent self-tuning methods on the basis of visualization. The principles of Grapheur were originated from researches on Reactive Search Optimization.
Reconsidering the Multiple Criteria Decision Making Problems of Construction Workers With Smart Eyes.
FROM DATA TO INSIGHT FOR BETTER DECISIONS! We are dealing with a series of multiple criteria decision making problems and analysis related to Canadian construction projects including waste management, productivity improvement, human and IT factors, emergy based lifecycle, and process optimization. As the data-sets of our problems are often huge they cannot be easily handled with the traditional means of visualization.
MAKING THE MOST OF OUR COLLECTED DATA WITH THE AID OF GRAPHEUR, THE BUSINESS INTELLIGENCE AND VISUALIZATION SOFTWARE
From data to insight ! The 7D plots and the option of sweeping through data have been found very useful for our applications. The achieved hidden information through Grapheur’s visualization tools would enhance our further decisions.
Grapheur, the flexible and powerful business intelligence and visualization, has brought all dimensions and criteria of the problems into our consideration at once. A team of managers then observes the 7D plots and sweeping animations for making the final decisions.
Here the idea for solving the multiple criteria decision making problems is to visually and effectively model and clarify the whole dimension of problems. For instance we are trying to find out with which rate and how, the workers’ level of skills should increase in order to maintain their performance with regard to team perceptions of supervision.
MAKING THE MOST OF OUR COLLECTED DATA FOR INFORMED DECISIONS!
PRODUCTIVITY IMPROVEMENT AND HUMAN FACTORS IN CONSTRUCTION PROJECTS
With the aid of data mining and visualization , provided by Grapheur, the hidden information are achieved which enhance the solving process of the multiple criteria decision making problems of construction project managements. After clarifying the dimension of the problems and finding out the relations between parameters and objectives, effective decisions are easier made.
CLUSTERING FOR A DEEP UNDERSTANDING!
The workers are surveyed with questionnaires and observations 1. Each row of our data-set is a construction worker with the corresponding columns, characterized by a series of parameters. For data analysis and visualization we use Grapheur and reconsider the problems this time with the open eyes. The 7D plots are widely used to screen the mined useful information. The numerous characteristics associated with the productivity and human factors with respect to productivity improvement are clearly visualized with the 7D plots.
DISPLAYING AND TRACKING THE PRECISE CONDITION OF CONSTRUCTION WORKERS IN THE PROJECTS We have found clustering tool very useful for a deep understanding of the different groups of workers. In this case workers are grouped according to the given characteristics.
PARALLEL FILTERS ARE OUR PREFERED TOOL FOR MULTIOBJECTIVE OPTIMIZATION.
The colored bubble chart is the most powerful tool for visualization the condition of the construction workers including numerous parameters. For instance in a particular visualization the work time vs. specialization of workers is graphed. Additionally the color code, size and the shape of the bubbles represent looking for material, idleness and looking for tool characteristics. In the bubble chart the option of sweeping through data is other useful visualization tool for tracking and analysis the workers’ performance.
A STUDY CASE- PROVIDING A RELIABLE WAY TO FIND THE MOST PRODUCTIVE WORKERS The parallel filters graph is very useful tool for multi-objective optimization. We can filter the results to select those which better fulfill our objectives. For instance we would start from the matrix of work time in a multidimensional space while aiming at filtering particular workers and examining their performance within a particular group e.g. those who have had maximum idleness characteristic.
With the aid of the 7D plots the characteristics associated with the productivity come to our consideration within a single graph. In our case the size, the color and the shape of the bubbles relatively displays the specialization, the moving, and the following the instruction characteristic of the workers. Moreover the blinking feature displays the idleness characteristic of the workers who have been idle less than 100 hours.
1 Roberto Battiti and Mauro Brunato, Reactive Business Intelligence. From Data to Models to Insight, Reactive Search Srl, Italy, February 2011. 2 Hewage K.N., Gannoruwa A., Ruwanpura J.Y. (2011), Current Status of Factors Leading to Team Performance of On-Site Construction Professionals in Alberta Building Construction Projects, Canadian Journal of Civil Engineering.
