The Italian trade association for the manufacturers of plastics and rubber processing machinery, Amaplast, is predicting a negative year-end result based on the figures for the period January-September 2020 and persisting economic fallout from the coronavirus pandemic.
According to the association, foreign trade data from ISTAT, the the largest producer of statistical information in Italy indicated a 17% drop in imports and and a 14% drop in exports ffor the first nine months of last year, compared to the same period in 2019. While still positive at over €1.3 billion, the trade surplus nonetheless showed a thirteen point contraction.
The year was characterised by a rough beginning, which particularly affected the domestic market. Although the situation improved somewhat after the trough in May, total production for 2020 is likely to be in the neighbourhood of €3.6 billion, an 18% fall against the €4.4 billion reported in 2019, estimated the AMAPLAST Statistical Studies Centre.
A similar result is expected in the consolidated year-end results for foreign trade. Looking at the geographical markets, Asia and North America have lost ground, while the market in Europe has strengthened somewhat.
These results were entirely predictable, given the global economic impact of COVID19. Moreover, there are as yet no signs that the pandemic will abate in the short term. As the second or even third wave sweeps the country, machinery manufacturers are increasingly adapting. Some have successfully introduced complex remote installation and maintenance procedures, ensuring their customers production continuity, particularly in sectors - such as packaging and medical - that have suffered less from the crisis. Moreover, the cost savings deriving from reduced in-person technical service may be an important innovation for the future.
These developments have also been facilitated by the ongoing research and development in Industry 4.0 features and interconnected production environments. As well, digitalisation is enabling the collection of huge volumes of data, for use in, among other things, optimising production line performance.