Home Editor's Choice Emerging technologies including AI can revive manufacturing sector

Emerging technologies including AI can revive manufacturing sector

Emerging technologies including AI can revive manufacturing sector

Traditional resource-based manufacturing industries are moving from high-cost developed countries to low-cost developing countries. In fact, one criterion for development is the dominance of service industries such as banking, insurance and distribution services over the manufacturing sector. As we are seeing now, dependence on service industries alone can lead to very serious problems.

Knowledge Based Industries and Developed Nations

Developed countries have a much better infrastructure for education, training and research, all of which are key inputs to develop an environment for knowledge-based innovation. By building on this advantage, they can rebuild a strong manufacturing sector. It is manufacturing that adds solid wealth in the economy, unlike excessive speculation and extremely complicated financial instruments.

European Union’s MANUFUTURE High Level Group of experts has already begun discussions to “transform manufacturing from a resource-based to a knowledge-based activity delivering products of higher added value”. One of their main responsibilities is to “improve the public image of manufacturing in order to attract and retain future talent capable of generating and applying the new knowledge”.

In this article, we look at the top emerging technologies.

NBIC – the Emerging Technologies

NBIC stands for Nanotechnology, Biotechnology, Information technology and Cognitive science.

Nanotechnology: “Nano-technology mainly consists of the processing of, separation, consolidation, and deformation of materials by one atom or by one molecule.” – Norio Taniguchi, 1974. It seeks to develop materials or devices of 100 nanometers or smaller. At nano levels, the properties of materials change (often with unpredictable side effects such a toxicity). These changed properties can come in useful in electronics, medicine and solar panels, for example. Nanotechnology is more a promise than reality now, however.

Biotechnology: “Any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use.” – United Nations Convention on Biological Diversity. It started with modifications of native plants into improved food crops through artificial selection and hybridization. Pharma products, crops with improved yields and resistance to environment, and food with increased nutrition, taste, texture and appearance are some of the areas where biotechnology is used now.

Information Technology: IT is “the study, design, development, implementation, support or management of computer-based information systems, particularly software applications and computer hardware.” Information Technology Association of America. It is practiced through computer hardware engineering, designing software and databases, networking, data management, and management and administration of information systems. Applications are numerous, and include Internet business, MIS, cellular hardware, 3G networks, electronic products, IT services, gaming and security.

Cognitive Science: It is defined as the study of the nature of intelligence, and draws upon varied disciplines such as psychology, philosophy, linguistics, anthropology, computer science, sociology and biology. Cognitive science helps with such human issues as attention, learning and development, memory, perception and language processing, as well as issues like artificial intelligence.

Emerging technologies promise a manufacturing scenario where knowledge is more important than raw materials and labor. This has the potential of providing a solution to the problem of job losses in developed countries caused by the movement of traditional manufacturing to low cost developing countries.

Shell Programming in Expert Systems Applications

Expert Systems are artificial intelligence programs that apply logical arguments to a knowledge-base. Prior to the use of expert systems, and other AI applications, the data in a knowledge base could only be interpreted and used by the human brain. The use of expert systems provides a means to access and utilize the information stored without the need for human involvement. These systems, which use small processes called shells, have limitations, but can provide benefits to the business world, particularly in the area of Help-desk technology.

Shells in ES Software

ES Software typically contains shells for each domain of knowledge in the knowledge-base system. For example, in a Help-Desk Expert System, one shell might encompass all of the knowledge needed to solve the problem if an Internet user called in to ask for help with a non-functioning Internet connection. Within one shell is all of the information needed to troubleshoot a DSL connection. The shell also contains a user interface, that asks questions to lead the shell to the correct conclusion. In between the user interface and the stored data is an inference engine, which decides which questions are appropriate, based on information already received.

In this example, the first question asked by the shell might be, “Is the modem’s power light on?” If the user responds negatively, the shell can conclude, with some degree of certainty, that the problem is due to a lack of power to the DSL modem. If the user responds that the power light is on, the shell can assume that the problem is not due to a lack of power. At that time, the shell will automatically rule out all possibilities that include power problems.

With each ensuing question and answer, the shell uses a previously identified set of rules to eliminate more potential answers, until reaching a conclusion based on the information provided and the rules set forth by the programmers.

Limitations of Expert Systems Applications

The limitations of expert systems applications lie in the input received. ES Software does not learn from experience, as a Neural Network does. An expert system receives knowledge as data input by experts, so the conclusions it reaches are only as good as the data it has been programmed with. In addition, in order to solve problems, it relies on answers and information received from a user. If the user enters inaccurate information, the expert system is unable to compensate for it. Finally, the rules set forth by the programmer influence the results reached by the shell.

An expert system is a perfect example of the phrase, “Garbage In, Garbage Out”. While expert systems have limitations, they are beneficial when executed carefully. If the information provided to the program is accurate, and the rules used to reach conclusions are logical, the shells can work together to reach logical conclusions for any situation they are programmed to address.