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RPA Interview Questions
The RPA lifecycle is the structure of how automation is delivered and executed. It consists of every one of the phases a bot goes through: from identifying a business process or task to automate through to its deployment as a bot in production and its continuous monitoring thereafter.
 
RPA lifecycle management refers to how each stage of a bot’s life is managed to ensure that it delivers the value to the business that was expected. It provides a framework for process automation to ensure the bot is designed to fulfill its requirements. It also offers a segmented process to ensure each stage of RPA delivery can be assessed and improved to enhance execution and performance.
There are seven stages in the RPA lifecycle:

RPA Lifecycle Management

1 - RPA Candidate Identification
In this stage, RPA stakeholders identify business processes and tasks that are good candidates for automation. The use of process discovery, task mining, or process mining tools may be used to uncover and produce candidates.
 
2 - Assessment & Prioritization
In the assessment and prioritization phase, business processes and tasks identified as candidates for automation are assessed and prioritized for design and development. The assessment involves technical feasibility. For example, suppose the task or process requires too many decisions to be made or interacts with too many systems increasing its dependency complexity. In that case, it may not be a good candidate for automation.
 
3 - Design
Design as a stage in RPA lifecycle management involves defining and modeling the actual process or task to be automated and mapping any dependencies that the automation might have, like the systems it interacts with or regulations that impact it.
 
The design phase provides a blueprint for the RPA developer to understand what needs to be automated.
 
4 – Development
In the development stage of the RPA lifecycle, the RPA developer builds the bot in the studio of the RPA platform your automation program has enlisted, according to the requirements and definition provided in the design phase.
 
Again, using a paper-based document like a PDD is not an optimal mechanism to drive development.
 
5 – Testing
In this stage, the RPA developer or QA team tests the automated process in a staging or testing environment to ensure it executes and performs as expected.
 
6 - Deployment
Once testing is completed, the bot is deployed in production and runs as configured in the RPA tool’s orchestrator.
 
7 - Monitoring & Change Management
In the final stage of RPA lifecycle management, the bot is continuously monitored to assess performance and ensure it runs without any errors.

Source : Blueprintsys 
It goes without saying that RPA isn’t a set it and forget it technology. RPA is essentially software built on top of other software. Each bot has a multitude of interactions with different systems and is impacted by any change to those systems.
 
Each stage of the RPA lifecycle will impact the bot’s uptime and ability to continually deliver the value RPA promises.
 
Many of the pain points RPA programs are experiencing today can be traced back to sub-optimal practices during every stage of the RPA lifecycle. For example, bots must be explicitly connected and mapped to their dependencies to enable proactive change management when an impending change to a legacy system or regulation impacts a bot in the future, which it will. This ensures the bot doesn’t just break and sit idle while its break is investigated, corrected, tested, and redeployed.
 
The good news is that it doesn’t have to be that way. Improved RPA uptime and greater returns are easily attainable with the right solutions and the addition of some best practices in your RPA lifecycle management.
Let's look at the difference between attended and unattended automation.
Attended Automation Unattended Automation
When complete automation of the end-to-end process is not possible, attended automation is used. In this scenario, attended bots collaborate with humans via system-level events that allow them to share data with human workers. Attended robots to optimize tasks by unloading portions of them and assisting in the completion of work. For example, during a live call with people in a bank, an Attended robot can gather data and enter it into another required form. This type of automation completes the task without the need for human intervention. Robots can be actuated by events and schedules in this instance. Unattended robots can work without human involvement 24 hours a day, 7 days a week, 365 days a year. For instance, a batch job to populate data on a server spreadsheet.
Employees activate a bot and interact with it as it provides assistance. Managers can coordinate tasks across internal resources and organize tasks between people and machines. Unattended RPA bots complete tasks on their own, following a set of rules.
Attended RPA bots are right there waiting for staff to activate them anytime they are needed to speed up the process. Unattended RPA bots follow a preset routine or are triggered by logic in the process flow.
Logs are time-stamped files that contain application-related information, error, and warning messages. The following are the two sorts of logs :
 
* Default logs : Default logs are created by default when a project's execution begins and ends, when a system problem occurs and the execution stops, or when the logging settings are set up to log every activity's execution. This category logs the following events : 

Execution start : It is generated every time a process begins.
Execution end : It is generated every time a process terminates.
Transaction start : It is generated every time a transaction within a process begins.
Transaction end : It is generated every time a transaction within a process terminates.
Error log : It is generated every time execution is ceased by an error.
Debugging log : It is generated if the Robot Logging Setting is turned to Verbose and contains activity names, types, variable values, arguments, and other information.

* User-defined logs : When using the Log Message action or the Write Line activity, user-defined logs are generated according to the process defined by the user in Studio.
Criteria Robotic Process Automation Traditional Automation
Technology It is non-instructive, scalable, and versatile. It is instructive, less scalable, and less versatile.
Use It is used to mimic repetitive and rule-based human actions. It is used to execute the pre-defined programmatic instructions.
Implementation It offers quick implementation. It takes less amount of time as compared to traditional automation. It takes several months for implementation.
Cost It seems costly in starting, but it is cost-saving technology in the long run. It seems cheaper in the starting but costs more in the long run.
Criteria Robotic Process Automation Artificial Intelligence
Use It is used to mimic repetitive and rule-based human actions. It is the simulation of human intelligence in machines that are programmed to think like humans.
Implementation It provides a smooth implementation. It can be set up within a few weeks. It does not provide the smooth implementation. It requires a lot of work to set up and run.
Concept It is based on pre-defined rules that help software bots to mimic human actions. It is based on 'thinking' and 'learning'. It can learn from human actions and make decisions on specific cases.
1. Unattended/Autonomous RPA : Ideal for reducing work like completing data processing tasks in the background. They don’t require any human intervention. These bots can be launched using: 
 
* Specified intervals
* Bot-initiated
* Data input

2. Attended RPA : These bots live on the user’s machine and are triggered by the user. They can be launched:
 
* When embedded on an employee’s device
* Automatically based on predefined conditions
* Leveraging an RPA client tool

3. Hybrid RPA : This is a combination of attended and autonomous bots. These bots address front- and back-office tasks in the enterprise 
Bot creator tools, such as Automation Anywhere or UiPath, are used to create bots that are used to automate processes or tasks. The following steps are involved in the creating a bot:
 
* Record a task
* Complete the bot implementation
* Test the bot
* Upload the bot to perform the automation tasks
Features TaskBot MetaBot IQBot
Core competency Used in frontend Facilitates scalability with next-gen integration Continuous learning and enhancing process automation
Used For repetitive and rule-based tasks In complex and scalable processes To manage fuzzy rules
Example HR administration, procure-to-pay, quote-to-cash, etc. Enterprise-wide automation; requires only minimal maintenance Real-time learning, extracting languages from the given data, etc.