July/August 2013
Workforce Development

Automation competency model serves emerging industry and professional needs

By Rajabahadur V. Arcot

The global economic evolution, triggered by industrialization, contributed to the emergence of demand-centric consumption centers and manufacturing industrial clusters. While technological inventions and breakthroughs spurred the growth of the manufacturing industry, the global economic expansion caused not only new demand centers but also led to a broad portfolio of industrial products and goods that cater to basic needs and aspirational wants. Additionally, continually advancing technological developments have tremendously influenced our lives and changed the manufacturing industry paradigm.

The initial thrust of the industrial companies was to identify the emerging needs and to use the available knowledge and technologies to develop and introduce new products. As the economies and markets expanded and competition intensified, manufacturing companies sought to gain competitiveness by differentiation and by focusing on improving quality and productivity, adding functionality to delight customers. The stage was thus set for companies to improve productivity and reduce costs even more by using automation.

Information technology

For their part, automation suppliers introduced new products that met the manufacturing industry's need for accuracy, repeatability, reliability, and other performance parameters. In many instances, suppliers led from the front in harnessing or adopting the technological innovations. The advent of computers spurred automation suppliers to embrace information technology (IT). The rapid development of information technology provided the impetus to incorporate processing and communication features in automation systems. With microprocessors becoming more reliable, powerful, and cheaper, and with software coming to the center stage, IT emerged as the backbone of plant automation systems, such as distributed control systems in process industries, programmable logic controllers in discrete industries, and supervisory control and data acquisition in remotely operated pipeline and electrical transmission and distribution industries. IT became ubiquitous, resulting in the widespread deployment and rapid development of hardware, software, and applications. While helping the automation companies take a quantum leap forward, the developments in the IT domain integrated automation more closely with information technology.

As competition among industrial companies intensified, they needed to integrate all the enterprise operations tightly along the value chain. As a result, automation expanded beyond the shop or the plant floor and was integrated with enterprise solutions to cover almost all aspects of enterprise operations. At the corporate level, IT managed numerous other processes, such as asset management, product life-cycle management, enterprise planning, and supply chain management. These trends caused industrial automation firms to continually innovate and remain in synch with the rapid developments in the emerging technological and business domains, especially the underlying technology, which is IT (hardware, software, and applications). Initially, industrial automation companies used proprietary hardware and software, but later they began to use commercially available off-the-shelf technologies, and the trend continues.

Industrial growth trends

Over time, industrial growth and economic expansion depleted natural resources and materials. Meeting increasing needs and wants has spurred the demand not only for a range of products, but also for resources, such as energy, minerals, and water. The realization that these resources are scarce forces companies to realign manufacturing strategies to increase resource efficiency and productivity, supply chain efficiency, and waste reduction. Developing sustainable manufacturing practices is the major challenge confronting the manufacturing industry. Additionally, due to the aging workforce and better career opportunities in service sectors, the manufacturing industry faces serious challenges in human resources. These challenges lay out the roadmap for the future of the manufacturing industry and have drawn the attention of thought leaders and think tanks.

The report Factories of the Future Public-Private Partnership, prepared by the Ad-hoc Industrial Advisory Group of the European Commission, focuses on the development of the next generation of production technologies and highlights the importance of sustainability and the need to leverage information-communication technologies to achieve intelligent manufacturing.

The World Economic Forum report The Future of Manufacturing Opportunities to Drive Economic Growth  highlights challenges, such as the growing competition and scarcity for materials resources, affordable clean energy strategies, and the ability to innovate at an accelerated pace, that will require the attention and collaboration of policy makers, civil society, and business leaders.

In its report Implementing 21st Century Smart Manufacturing,  the U.S.-based Smart Manufacturing Leadership Coalition discusses the drivers of change in manufacturing, lays out the blueprint for the future of the industry, and identifies the essential technologies. These include intelligent automation, networked sensors, data interoperability, multiscale dynamic modeling and simulation, and scalable, multilevel cybersecurity system protection from cyber-vulnerabilities.

The report Recommendations for Implementation, prepared under the coordination of the German government's Federal Ministry of Education and Research and the Federal Ministry of Economics and Technology, makes comprehensive strategic recommendations for ensuring Germany's Industry 4.0readiness. The term Industry 4.0  refers to the extension of the industrial era, which started in the late 18th century, into the 21st century. The invention and widespread use of the steam engine and coal for energy, the growth of infrastructure industries (i.e., electric power, steel, and oil), and the widespread use of computers and microprocessors are considered to be the first three phases of industrialization. The report looks at the emerging industrial landscape that would be dominated by intelligent machines, embedded cyber-physical sensors, networked processes, collaborative technologies, and the extensive application of enterprise-wide automation.

Emerging manufacturing era

Industrial automation has a major role in empowering manufacturing companies to succeed in the emerging information- and knowledge-based manufacturing industry era, call it smart manufacturing, factory of the future, sustainable manufacturing, or Industry 4.0. The future belongs to those companies that recognize automation's pivotal role. While this realization spurs companies to increase their

automation investments, the growth of the automation industry and the success of automation projects depend not only on technology, but also on the human resources that industrial automation companies, their system integrators, and end user companies require. Ultimate success depends on the competency of the automation professionals. Right now there is a wide gap between the competencies of professionals coming out of academic institutions and industry's expectations of them. It is time for all stakeholders to give serious consideration to improving the situation. Fortuitously, there are some important developments at the global level to provide direction.

Automation Competency Model

The Automation Federation (AF) and the U.S. Department of Labor have developed an appropriate competency model for automation professionals. The Employment and Training Administration of the U.S. Department of Labor is concerned with challenges related to the aging workforce. A competency model is a clear description of the abilities, knowledge, and skills required to perform well in an occupation, and the automation competency model (ACM) describes what a person needs to know and do to successfully perform the tasks required in automation careers.


The model comprehensively classifies the competency requirements from various perspectives, such as personal effectiveness, workplace, industry, automation technology, occupational, management, and others. Within each competency tier, the model identifies the required skills. For example, ACM identifies reading, writing, mathematics, science, communication (listening and speaking), critical and analytic thinking, and computer knowledge as essential skills from the personal effectiveness competency perspective. Automation technology continually evolves and is multidisciplinary, and therefore close collaboration among all the stakeholders is necessary to ensure the competency level of automation professionals continually remains high.

The intent behind the development of the model is threefold: prepare those interested in pursuing job opportunities in the automation profession, help companies in their workforce enablement efforts, and assist academic institutions in updating curricula to better prepare the technology workforce for the future. The ACM provides a common language for the dialogue among the stakeholders-automation professionals, academia, and industry.AF and ISA work closely to build strategic partnerships with academic, industry, government, and private groups that will expand the use of the automation competency model globally.


auto1112Rajabahadur V. Arcot (rajabahadurav@gmail.com) is an independent industry analyst/columnist and automation consultant with approximately 40 years of senior managerial experience. He has held C-level executive positions in leading companies, such as Honeywell, Thermax, Bells Controls (an affiliate of Foxboro/Invensys), Electronics Corporation of India Limited, and Instrumentation Limited. Until recently, he was responsible for ARC Advisory Group's business operations in India.