Outline

  • Abstract
  • Keywords
  • 1. Introduction
  • 2. Evolution of Data Warehouses in Infrastructure Management
  • 3. Structural Design for the Sewer Data Warehouse
  • 4. Multidimensional Modeling for the Sewer Data Warehouse
  • 5. Development of the Decision Support System for Sewer Infrastructure
  • 6. Potential Benefits for Existing Sewer Infrastructure Management Systems
  • 7. Conclusions
  • Acknowledgment
  • References

رئوس مطالب

  • چکیده
  • کلید واژه ها
  • 1. مقدمه
  • 2. تکامل انبارهای داده در مدیریت زیرساخت
  • 3. طراحی ساختاری یا سازه ای برای انبار داده فاضلاب
  • 4. مدلسازی چند بعدی برای انبار داده فاضلاب
  • 5. توسعه سیستم پشتیبانی تصمیم برای زیرساخت فاضلاب
  • 6. مزایای بالقوه برای سیستم های مدیریت زیرساخت فاضلاب موجود
  • 7. نتیجه گیری

Abstract

Since the inception of the Governmental Accounting Standards Board statement-34 (GASB 34) in the United States, local and state governing entities need to inspect sewer systems and collect general information about their properties. Application of the collected information in decision-making processes, however, is often problematic due to the lack of consistency and completeness of infrastructure data. In addition, most techniques involved in decision-making processes are relatively complicated and difficult to implement without a certain level of engineering experience and training. Consequently, the sharing and transferring of pertinent information among stakeholders is not smooth and is frequently limited. This study presents a decision support system (DSS) for the management of sewer infrastructure using data warehousing technology. The proposed decision support system automatically assigns appropriate inspection and renewal methods for each pipeline and estimates associated costs, resulting in effective and practical sewer infrastructure management from various perspectives, with corresponding levels of detail.

Keywords: - - - -

Conclusions

This study presents a simplified decision support system with the combination of a data warehouse and decision supporting modules. Efficient data structures, such as the bus matrix and star schema, were suggested in the optimal data warehouse for sewer infrastructure management. The data warehouse was connected with the decision supporting modules for strategic decisions about the inspection and renewal of pipelines, and the decision/estimation module determined the appropriate inspection and renewal methods as well as the associated costs under given conditions.

The VBA and Excel platforms provided a simple but powerful environment for data analysis. Despite the simplicity of the system, it could perform an outstanding job with general infrastructure information, such as pipe properties and defect codes, which were readily accessible for most agencies. In addition, the system could easily be utilized without arduous training or high-level expertise about the processes or structure of the system. However, the proposed system has some limitations. First, the decision criteria for the selection of inspection and renewal techniques may have to be refined to satisfy the particular site conditions of the infrastructure. For example, applicability of the techniques according to material types and diameter range needs to be verified and reflected in the system based on the most up-to-date information. Second, the proposed system currently recognizes only one defect in each pipeline. The proposed system may not be effective in the case where the pipeline has more than one defect and each defect should be handled with a different technique. Considering these deficiencies, further study is required to improve the applicability and accuracy of the system based on more real-life data. The proposed system is expected to significantly advance current practices of investment decisions for sewer infrastructure management, especially when the database is periodically updated for a comprehensive list of available inspection and renewal techniques, vendors, and prices.

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