一家大型制造厂开发了一套信息系统来描述 并追踪垃圾排放。其中一个系统关注工业领域的资产 下水道系统。开发了一个空间决策支持系统（SDSS）来记录 并跟踪有关通过IS排放的所有废物以及IS资产的信息 他们自己该公司排放废物的能力取决于信息 在最近一次结构检查期间获得的信息表明，废物将流动 通过准确和最新的检查数据对设备的功能至关重要 SDS用于监管报告和资本改善的内部决策。 因为技术和业务规则在系统启用后发生了重大变化 最初建造的这些系统正在重新设计为一个单一的集成系统 系统具有通用的数据库平台。业务建模是 系统重新设计。有许多复杂的规则指导信息系统的管理 资产为了组织业务建模工作，已经开发了7个一般业务流程 已确认。这些措施包括: 检查数据记录； 检查计划和日程安排； 地图绘制和空间查询； 报告； 下水道审批流程； 数据维护；和 资产的优先顺序。 本文介绍了用于对这些业务流程建模的方法 以及检验数据记录（IDL）业务模型的案例研究，以及它在 系统设计和开发。检查数据记录过程包括以下步骤: 有趣的因素，例如在存储到数据库之前需要验证数据，以及 需要对IS资产进行分类，以跟踪设施长期释放的进度 预防计划。

A large manufacturing facility has developed a set of information systems to characterize and track waste discharges. One of the systems focuses on the assets in the industrial sewer (IS) system. A spatial decision support system (SDSS) was developed to record and track information about all waste discharged through the IS, and about the IS assets themselves. The company's ability to discharge waste is dependent upon information obtained during the most recent inspection of the IS structures that the waste will flow through. Accurate and up to date inspection data is critical to the functionality of the SDSS for regulatory reporting and internal decision making about capital improvements. Because technology and business rules have changed significantly since the systems were originally built, the systems are in the process of being redesigned into a single integrated system with a common database platform. Business modeling is a key component of the system redesign. There are a number of complex rules guiding the management of IS assets. To organize business modeling efforts, 7 general business processes have been identified. These include: Inspection Data Logging; Inspection Planning and Scheduling; Mapping and Spatial Queries; Reporting; Sewer Approval Process; Data Maintenance; and, Prioritization of Assets. This paper presents the methodology used to model these business processes and a case study of the Inspection Data Logging (IDL) business model, and its use in system design and development. The Inspection Data Logging process includes a number of interesting factors such as the need to validate data prior to storage in the database, and the need to categorize the IS assets to track progress with the facility's long term release prevention program.