Manufacturers continue to invest in technology that can accelerate output while driving heightened productivity. Take D’Addario, a Farmingdale, N.Y.-based maker of musical strings for instruments such as cellos and guitars, for example.
D’Addario operates a 110,000-square-foot lean manufacturing facility that relies on robotics, software, and other advanced technologies to help it increase productivity, operate more efficiently, and compete more effectively in the global marketplace.
Increasingly, manufacturers are turning to emerging technologies such as 3D printing, which can take a digital file and turn it into a physical object. But the technology, which has been around for 30 years is still nonetheless very much in its infancy.
Two years ago, doctors at the University of Michigan saved the life of a premature infant by implanting a 3D printed lung splint into his windpipe. Last year, the first 3D printed gun was fired at a test location in Texas.
It’s true that 3D printing and other emerging technologies offer tremendous promise for manufacturers to slash costs, speed innovation, and drive operational efficiencies. But a new white paper from Frost & Sullivan underscores the fact that many manufacturers lack mature, robust processes for identifying and evaluating the impact of emerging technologies on their competitiveness.
Manufacturers that lack the maturity to identify whether new technologies are good fits for their organizations and their business goals can utilize predictive analytics to explore these capabilities in a number of ways.
For instance, a manufacturer can apply analytics to plant floor performance data to identify areas that are either underperforming or could be further strengthened by the use of a particular technology. Analytical tools may help a parts maker recognize an opportunity to significantly reduce material waste by implementing technologies that allow the firm to reuse materials.
By 2030, some 30% of the world’s demand for resources could be met through resource efficiency improvements, according to McKinsey & Co. Further analysis by the parts maker can help determine the returns from investing in material reuse technologies and the business impact that can be generated from a specific capital outlay.
Meanwhile, the use of analytics tools can also help manufacturers identify their most pressing business or operational requirements, which can then be used to determine the types of technologies that can best address these needs.
For example, if the top business goal for a manufacturer of beef products is to increase revenue, big data analytics can be used to help the company identify the least profitable products it produces.
In addition, analytics can help the company determine whether there are advanced manufacturing technologies available that could potentially be used to retrofit its plant floor operations and manufacture products that carry much higher profit margins, such as poultry-based products.
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