5Robotics and smart machines in enterprises

Smart machines are a subset of artificial intelligence that can teach themselves how to do things and perform tasks. These machines are moving toward digital, using artificial intelligence and machine learning to its full potential. Artificial intelligence (AI) is what makes these machines to appear intelligent and provides the framework for smart machines to function. Smart machines include robots, self-driving cars and other systems that are designed to work through tasks without human intervention. In business such technologies are expected to bring higher profit margins and lead to more efficient manufacturing processes. However, smart machines are also expected to displace workers and dramatically change the nature of work and other societal norms. Today's smart machines might seem revolutionary, like something in science fiction movies (like C-3PO in Star Wars). However, smart machines are the next step in a long history of incremental advancements in machines and computing. Smart machines could trace their roots back to the first Industrial Revolution (the 18th century), when the rudimentary machines were used to automate some human tasks. The advent of computers in the 20th century together with rise of Internet of things, data storage systems and sensors enabled collection and analysis of huge data volumes, further speeding the rise of smart machines. Such huge data volumes can be effectively exploited using data analysis methods. Big data analytics refers to a method for gathering and understanding large data sets in terms of what are known as the three V's, velocity, variety and volume. Velocity informs the frequency of data acquisition, which can be concurrent with the application of previous data. Variety describes the different types of data that may be handled. Volume represents the amount of data. Data can be also exploited by business intelligence (BI) and advanced analytics, whereby computers run algorithms to analyse data to identify patterns and then to use those patterns to generate insights into past and current events and, later, to offer insights on what would happen and what could happen if certain future actions were taken. This analytics capability, in turn, led to machine learning and deep learning, where computers themselves actually learn from additional data sets; more to the point, these smart machines use their new knowledge to adapt and adjust their output.

In medicine area, a lot of other people are talking about how to get an AI / computer with machine learning algorithms to diagnose patients or to replace physicians, but it is about augmenting the physician, to use the computer as a tool rather than a replacement. E.g. in experiments [31] when a patient is triaged by a nurse, the data captured is run through a predictive analytics engine, which determines the top five chief complaints a patient most likely has. The program has improved collection rates of chief complaint data dramatically - from 25% to 95%.

Robotics is a type of engineering that is behind the design and operations of robot machines that can perform tasks without human aid. This is one tool under the umbrella of smart machines. According to Gartner, they must be able to:

- adapt their behaviour based on experience (learning),
- not be totally dependent on instructions from people (learn on their own),
- be able to come up with unanticipated results.

Learning on their own in a variety of different environments has set robots up to be vital tools in some leading industries. Among these are:

- Healthcare - robots have been seen in different areas of the healthcare industry such as surgical care and doctors tasks. The evolution of healthcare involves robots in a major way and experts say it is only going to expand. Robots are seen in surgical care because they provide the precision, flexibility and detail focused manpower that assists doctors in order to make surgeries seamless and effective.
- Finance - financial services use robotics in order to carry out different operations. Robo-advisory firms have become the future of banking. They simply use unique and sensitive algorithms that provide services such as financial advice and portfolio management. These firms offer customers a personalized experience and bridge the divide between financial services and digital. Forbes agrees.
- Rtail - robotics is being applied for in-store customer service. This is seen in a variety of stores who provide interactive tools that customers use in order to shop for a product in the store or to gain access to an employee quickly.

Fig. 13 Baxter, robot, Rethink Robotics

When deploying the robots in the industry, there is important problem - the human-robot barrier. In most cases now, robots working on the factory line are kept in cages because they pose too many physical risks to humans, which causes that the human workflow is completely separated from the robot workflow.

There is on-going effort to achieve the human and the robot to train together, to create a shared understanding of how to work together and be more efficient. An early example is the Baxter robot built by Rethink Robotics. Baxter, built in a human form, can work right next to line employees on the factory floor - without a cage. Several factories have deployed Baxter to perform "dull jobs" - highly repeated tasks such as precision packing. Baxter is equipped with sensors that enable the robot to "feel" and "see" so it can adapt to its environment. It is not needed to tell him how fast a conveyer belt is moving; he sees it; he knows it and has common sense to figure that out. As robots become more integrated into the workflow, as smart machines begin to share a business process with humans, the data they absorb and generate becomes more important to the enterprise.

A new powerful element on the robotics and smart machines area is Cognitive Computing. It is clear that technology in robotics is moving toward innovative tools that use self-learning techniques in order to carry out tasks. Cognitive computing is among those tools that have been a disruptive force in the industry of smart machines. “Cognitive computing is based on self-learning systems that use machine-learning techniques to perform specific, human-like tasks in an intelligent way.” Cognitive computing stays true to what smart machines consist of - a form of artificial intelligence that allows us to make sense of the data that is processed through systems. It runs through a large amount of data that would take humans an immense amount of time to do. It then finds and creates actionable data instead of raw data, which means businesses can use the information presented in real time. This tool makes it easy for organizations to carry out operations because it gives data a purpose. With so much data being accumulated in the leading industries, using this tool makes the information found actually useful, therefore making systems to excel.

Another important notion is Smart manufacturing. It is a broad category of manufacturing with the goal of optimizing concept generation, production, and product transaction. While manufacturing can be defined as the multi-phase process of creating a product out of raw materials, smart manufacturing is a subset that employs computer control and high levels of adaptability. Smart manufacturing aims to take advantage of advanced information and manufacturing technologies to enable flexibility in physical processes to address a dynamic and global market. There is increased workforce training for such flexibility and use of the technology rather than specific tasks as is customary in traditional manufacturing.