In this globally competitive economy, finding ways to offer better quality products at lower cost has been the endless challenge to improve as well as sustain competitiveness. With the eroding human labour, exploitation of science has been the next frontier for growth. Although developed through long painstaking research, most of the useful scientific knowledge circulates freely. Developing countries can easily acquire them by making an affordable investment in education. But turning acquired knowledge into wealth through production of better quality products at lower cost has been a daunting challenge.
As a result, growing numbers of science graduates end up in unrelated jobs, virtually requiring no use of knowledge of natural science. On the other hand, developing profitable large-scale software business has been an unfulfilled dream for many developing countries like Bangladesh. Although India succeeded in creating almost 3.9 million export-oriented information technology service jobs, those jobs are on the path of erosion. Moreover, existing software development activities in developing countries mostly deal with database centric business application development, encoding virtually no knowledge of natural science in software. But there is an unfolding opportunity to blend science with software to develop machine capability, often termed as machine learning or artificial intelligence, to enhance existing productive activities--to produce better quality products at lower cost. Such blending strategy opens a new opportunity for competitiveness.
Let's clarify this opportunity of fusion of science with software through a simple example. Producing clay pots is an indigenous domestic industry of Bangladesh, like many other countries. Clay, soft and plastic type substance, when heated to a high enough temperature becomes hard and glass-like. Once the pot is formed on the rotating wheel, it is left to dry. Dried pots are backed in kilns. The glaze could be added to pots to add colour, texture or functionality. Glaze, after reaching the proper temperature, usually becomes a hard, glassy surface on the clay to increase the aesthetic properties and/or the functional capabilities. The quality, productivity, wastage and cost of production could be positively influenced at different stages of production, starting from clay preparation to proper heating, adapted to different types of glaze and clay type. The quality of clay pots depends on a number of factors including uniform baking (affected by the variation of moisture content), defects caused by the presence of trapped air bubbles and the surface smoothness. The cost of production primarily depends on the wastage of energy and marketable produced outputs, as many defective pots as high as 30 per cent are discarded after an expensive baking process. By improving the production process through innovations with the support of modern technology through the fusion of underlying science with software, better clay mould could be produced with uniform moisture content and less presence of air bubbles. Moreover, the quality of clay mould as well as raw clay pots could be checked through software-based thermal imaging technique to make sure that pots with the presence of trapped air bubbles are not backed to reduce the wastage. The uniform heating could be improved by adding in-kiln thermal sensors and software-intensive microcontroller-based control system. Such a process innovation leading to smart manufacturing has the potential to improve the quality, reduce the cost, generate higher profit and cause less harm to the environment, while creating high paying jobs for engineers for innovating better production processes-by blending science with software.
Similarly science of plant biology could be blended with software to process images of crop leafs with smartphones to precisely determine fertilizer need-opening the opportunity of wastage reduction. Numerous such examples could be cited. As a matter of fact, innovations in the form of robotics and automation are strongly relying on such opportunities. For example, automobile company like General Motor saved millions of dollars by interpreting data gathered from smart humidity sensors within the context of applicable scientific principals to determine whether automobiles can be painted. If the software by interpreting sensor data reveals that it is too humid, the car does not get painted at that time. Repainting time and expense are reduced and plant uptime is increased. As a matter of fact, smart or precision production basically leverages knowledge of the science of raw materials with software to optimise the production so that wastage gets reduced, efficiency increases and effectiveness of processing improves. Most of the developing countries are pursuing the technology of import driven strategy to benefit from such opportunity. But, such strategy fails to create high paying innovation jobs in the local economy. With the availability of low-cost sensors, computing processors and growing number of science and technology graduates, the alternative strategy could be to lead process innovation by blending science with software through local capacity improvement. Such strategy will improve the competitiveness of many local indigenous production processes as well.
Over the centuries, developing countries are facing extreme difficulties to turn knowledge of natural science into wealth. As a result, upon studying physics or biology most of the graduates end up in jobs having no relevance to those subjects. But the availability of micro sensors, processors and smartphones have opened the opportunity to turn the knowledge of natural sciences into the software to improve processes of whatever they are producing now--starting from tomatoes to fabrics.
To capitalise on this opportunity, science education should be blended with the purpose of improving local production processes by developing innovative software-intensive smart process capabilities. Instead of pursuing research for publication in competing with the West, the focus should be on partnering with local firms to innovate processes to produce better quality products at lower cost. The public policy should support both the supply and demand sides in creating the market for such software-intensive smart innovations. Incentives should be provided for targeted improvement of local production processes by fusing relevant knowledge of science with software, instead of just expanding science and technology education, and targeting export-oriented information technology service for the growth of the software industry in isolation. By improving competitiveness by even just 5 per cent per year through software and natural science-intensive process innovation, the overall economic benefit could be substantially large. It's time for developing countries to focus on software-intensive innovations to turn science into wealth through process improvement to enhance the quality and reduce the cost of production.
M Rokonuzzaman Ph.D is academic, researcher and activist on technology, innovation and policy. [email protected]
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