IEEE 2755.1:2019 pdf download.IEEE Guide for Taxonomy for Intelligent Process Automation Product Features and Functionality.
This guide dcfincs and classifies a Software-Based Intelligent Process Automation product’s capabilities and features in six major categories along with its underlying technology for the interested community.
1.3 Purpose
This guide creates clarity for all who are involved with Software-Based Intelligent Process Automation products so that industry panicipanb may rely on a product manufacturer’s functionality claims and understand the underlying technological methods used to produce those functions. This guide represents the conscn%us of a diverse panel olindustry panicipants.
2. Feature set description and definitions
2.1 General
A wide-ranging variety of available lrndligcnt Process Automation products were included in the analysis to identify a conistcnt taxonomy fbi the broad categories of design and functionality present in all or most products. The following six categories arc discussed in 2.1.1 through 2.1 6.
2.1.1 Architecture
The Architecture Feature Set explores the attributes of seven key areas, these being: supported infrastructure, scalahility. communications. reco cry and recilicnce. security. extensibility, and deployment options. It hac been rccognitcd thai an Intelligent Process Automation product’s architecture was in inherent component of all other feature sets. This gives context to a range of irnpactful dilkrenccs such as cloud versus desktop deployment models and static versus elastic rcsorcc provisioning.
2.1.2 Configuration, Build, Test
The Configuration. Huild. and Test Feature Set includes capabilities to develop and test configured aulotnalions. This includes such things as object libraries, available commands, graphical configuration en’. ironment. exception handling protocols, requirements descriptions, configuration build docUmernauofl, debugging, management of test environments, access and security, credential, .ind u-cr definition
2.1.3 Orchestration
The Orchesranon Feature Set describes the product’s capabilities that consumc sequencing logic, static and conditional business rules, internal or external predictive and prescriptive analytics (ML) and gather current state target systems infbrmation to properly coordinate all necessary tasks to complete a series of processes. and their associated transactions.
2.1.4 Management
The Management Fcaturc Set describes the abilities to: I) centrally control tasks / processes. provide access control to a variety of system resources such as tasks, devices and administrative duties, while ensuring availability of the platform; 2) manage central storage of tasks, system workload and pcrtonnancc. resource behavior, licensing and user behavior and 3) enable visibility of execution platthrni resources and processes. manage schedules, alerts, and log all aspects of automation.
2.1.5 Execution
The Execution Feature Set dcscnbcs the set of functions available in the product’s run-time environment that govern how a configured automation carries out its intended sequence of actions in the production software environment. This includes such things as: accessing target applications through a graphical user interface or application program interface, screen object recognition, consumption of pre-configured tasks and business logic, human attended process input, execution run-time logging, and exception handling and notification.
2.1.6 Intelligence
The Intelligence Feature Set evaluates the platform’s ability to consume and apply learning or prediction capabilities to aid in the orchestration of configured automations without being configured with each specific instruction or conditional business rule. This includes abilities to incorporate process-specific data and capabilities to automatically generate and select high performing machine learning (ML) models, inspect results, and make decisions.
NOTE For these purposes, Intelligence i% broadly defined as the usc of ML data models for a wide variety of purposes ranging from Optical Character Recognition (OCR) to process mining to Natural Language Processing (TsLP) to process orchcsirauon to esception prediction and others. IEEE 2755.1 pdf download.