System of rules integration problems and solutions to enterprise resource planing systems

A Business rules (BR) and business rules engine (BRE) enables an organization to increase its agility and speed to adapt to business process changes. This article analyzes business rules, business rules engines, and possibilitiesof their applying in resourcesmanagement systems used by enterprises.Ways of implementing business rules are discussed, considering peculiarities of business resources engines. The analysis shows that one of the ways to employ business rules is databasemanagementwith the help of triggers. An analysis of business rules engines is performed, and an extension realizing business rules transformation intoDBMS triggers is suggested.

Business process management (bpm) application through strategy, indicators and operations model (meio): a health service company case

Business Process Management (BPM) is an approach to analyze and improve main activities of a company continuously. It seeks consistent results aligned with the strategic objectives. There are several approaches to the application of BPM, which focus on specific aspects of the company, not meeting all their needs. The Strategy, Indicators and Operations Model (MEIO), developed by Müller (2003), compiles the fundamental points of each isolated approach, creating a single model. The objective of this work is to provide a step-by-step application of the BPM aspects of MEIO in a practical case: a reference company that provides health services. Also, it provides a framework for organizing and connecting the various components of a product or service to its value chain. Through MEIO, a general analyze of the Company under study was made and the process “payment of invoices from providers” was detailed. Improvements were suggested based on a deeper investigation of the activities involved. The results include: (i) creation of rules engine to validate the procedures to be launched according to coverage, shortage, and contract; (ii) receiving procedure and cost audits separately and; (iii) digitalization and automatization of repetitive and manual activities.

Dynamic Inference Approach Based on Rules Engine in Intelligent Edge Computing for Building Environment Control

Computation offloading enables intensive computational tasks in edge computing to be separated into multiple computing resources of the server to overcome hardware limitations. Deep learning derives the inference approach based on the learning approach with a volume of data using a sufficient computing resource. However, deploying the domain-specific inference approaches to edge computing provides intelligent services close to the edge of the networks. In this paper, we propose intelligent edge computing by providing a dynamic inference approach for building environment control. The dynamic inference approach is provided based on the rules engine that is deployed on the edge gateway to select an inference function by the triggered rule. The edge gateway is deployed in the entry of a network edge and provides comprehensive functions, including device management, device proxy, client service, intelligent service and rules engine. The functions are provided by microservices provider modules that enable flexibility, extensibility and light weight for offloading domain-specific solutions to the edge gateway. Additionally, the intelligent services can be updated through offloading the microservices provider module with the inference models. Then, using the rules engine, the edge gateway operates an intelligent scenario based on the deployed rule profile by requesting the inference model of the intelligent service provider. The inference models are derived by training the building user data with the deep learning model using the edge server, which provides a high-performance computing resource. The intelligent service provider includes inference models and provides intelligent functions in the edge gateway using a constrained hardware resource based on microservices. Moreover, for bridging the Internet of Things (IoT) device network to the Internet, the gateway provides device management and proxy to enable device access to web clients.

A Declarative Approach to Systems Development

The declarative approach specifies what is to be done rather than how to do it. When adopted in information systems development, this implies that the system should be seen as a collection of business rules that can be enacted using a business rules engine. Business rules should be expressed in a form that is as close to the one in which business people perceive the rules. A business rules management system is needed to acquire, store, and allow modification of a business rules database. The rules are then handed over to a rules engine for enactment. The BRMS considered in this chapter uses an antecedent-consequent form for representing rules. These are based in a first order logic. Rules are formed with courses of actions and conditions in rules antecedents and courses of actions in rule consequents. It also introduces notions of state change in the business rule and temporal relation within rule and between different rules. Business rules are structured into atomic, complex, and abstract rules. The business rules are translated into enactment rules and converted to Java.