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Posted on : Thursday 2nd April 2020 04:44 PM

Parsable: Key Drivers For Industrial Decisions In 2020


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To improve the productivity, quality and safety within industrial companies, the sector is expected to raise the priority of capturing human activity data, and to open up new opportunities for the application of machine learning.

For many years, machine learning was centered around using algorithms and models to identify patterns and make decisions with minimal human intervention.

Key steps made so far:

  1. The digitalisation of paper-based standard operating procedures to collect data.
  2. Data analysis: look at what, why and how something happened in order to identify trends and predict future behaviours.

New ways machine learning is being applied - which will be seen more throughout 2020 - is the interaction and exchange of human activity data with ‘intelligent’ machines and platforms, with human behaviour informing prescriptive next best actions.

“According to PwC, manufacturers’ adoption of machine learning and analytics to improve predictive maintenance will increase by 38% by 2022.”


Sustainability across the value chain

Parsable predicts that across the entire value chain, sustainability will be a key driver in technology decision making to improve operational efficiency and reducing waste, which will become mandatory.

Organisations no matter how big or small will be held accountable to maintain sustainability from customers, investors, partners and the general public. Something which is increasingly being used to define a trustworthy company. 


Batch of one

‘Batch of one’, is the new norm for manufacturing as the increase in consumers demanding choice, resulting in manufacturers being required to rapidly deploy agile and mobile-first worker platforms.

As companies gain greater visibility on their customer needs and wants, the manufacturing industry will be under pressure to address the niche markets and preferences faster than ever. However, many manufacturers are lacking the equipment designed to handle the variability. During 2020, companies will need to address ways to handle quicker transitions between production runs and how to make line changeovers a continuous exercise. However, in order to achieve this increased efficiency and agility, manufacturers could face an increase in potential equipment malfunction, safety incidents and deviations from standard operating procedures, something which they need to be prepared for.


Safety

As the correlation between safety to quality and overall operational efficiency becomes increasingly clear: Parsable highlights that Safety is becoming a true C-suite issue.

Whilst workplace safety should always be a top priority, in recent years workplace safety has increasingly come to the forefront of industry focus, and in 2020 this will reach new heights. Parsable predicts that the industry should see increased attention on safety culture, worker protection and regulations as the impact of safety on quality and efficiency becomes increasingly important.

From the top-down leaders will demand an increase in transparency and proactivity to enforce and improve worker safety, which will include the investment in technology. 


MANUFACTURING GLOBAL


Tags:
manufacturing global manufacturing industry industrial companies machine learning digitalisation of paper data analysis technology

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