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ADMA Smart Manufacturing explained

This is the first in a series of seven articles that the ADMA initiative will produce in order to present the current self-assessed maturities of manufacturing managers in relation to the seven dimensions that European enterprises can advance on in order to improve their manufacturing performances. The seven dimensions are:

  • Smart manufacturing
  • Advanced manufacturing technologies
  • Digital factory
  • Eco-factory
  • End-to-end customer-focused engineering
  • Human-centred organization
  • Value chain oriented open factory

The Belgian metal subcontractor Provan decided they we were going to distinguish themselves by producing smaller series of products and providing a wider range of products in less time. The unique QRM production strategy (Quick Response Manufacturing) formed the basis for this. They were one of the first European companies that fully took QRM on-board. The strategy reached throughout the organisation and focused on shortening the turnaround time. The emphasis always has been on ‘time’, not on ‘costs’, enabling the company to significantly decrease the Total Cost of Ownership. Provan organized itself to be able to process 3000 orders a month, without having a planning department inside the company! Every machine operator decides independently what he will produce next. Of course an intelligent ICT-system supports him taking the right decisions. As a result, work-in-progress inventory levels decreased by a factor 9 and assembly throughput times moved down from 4 weeks to 3 days!

The EASME financed ADMA initiative is helping manufacturers throughout Europe measure their manufacturing maturity in relation to seven advanced manufacturing dimensions. One of these dimensions is smart manufacturing which is described along five performance areas in the left column of the table below.   

The average maturity scores for smart manufacturing dimension as estimated by managers and employees in more than 30 European manufacturing SMEs are listed in the middle column.

The average performance levels are described in the right column.  

Smart manufacturing progression themesAvarage maturity levelsApproximate average Maturity levels
From rigid automation to flexible manufacturing: Shop floor people and intelligente machines work side by side on the shop floor for maximum flexibility 2,08Key manufacturing equipment and automation solutions are combined into Manufacturing Cells connected to a digital platform (level 2 of 5)
Shop floor tasks: Shop floor people, automations and intelligent machines work side by side on the shop floor for maximum efficiency2,23Specific repetitive and tedious manufacturing tasks are performed by industrial automations and/or robotic systems (leve 2 of 5)
Flexible and quick response: (self-managed) quick response planning and production systems enable the company to adapt quickly to changing orders and customer request whilst at the same time keeping short throughput times 2,97The company manufactures to order large batch sizes and/or minimises changeover times between batches using a manual, digitally supported manufacturing planning system. The feedback of customers and suppliers is sometimes used to improve manufacturing processes (level 3 of 5)
First time right: Self-managed quality and process control systems enable the company to adapt quickly to changing orders and customer requests without jeopardizing quality levels.2,43Quality inspection techniques and statistical models are used to improve quality (level 2 of 5)
KPI visualisation and management: Moving towards real-time smart manufacturing KPIs used to monitor, assess and improve the company’s performance.2,29A basic set of KPIs has been defined and they are monitored at quarterly intervals (levels 2 of 5)

The purpose of ADMA obviously is to help SMEs in the manufacturing sectors improve their business performance.

So what would your enterprise, if at this average maturity level, need to do to advance to advance to the next level in each of the performance areas and what would your enterprise potentially gain from that?    

In a move from rigid automation to flexible manufacturing, moving from maturity level 2 to level 3 would mean introducing/setting up digitalized machines to launch and perform simple and/or repetitive tasks in an automated way.

An example of a company for whom flexibility is key is Newtec. Each complex satellite communication product is customer-configured using pre-defined modules, which are almost daily adapted to the latest technological innovations. Newtec transformed itself to a digitised factory. Starting with digitising production instructions for a few thousands of different products to taking up the challenge of having all information at the right time at the right place in production. In the meantime, Newtec brings approx. 200 new products into production every year with a first pass yield level of >95%. Working for 7 years on lean pull systems, throughput times have been reduced from 9 to less than 5 working days and turnover per employee has risen by 25%.

In a move towards, setting up automations to allow employees and intelligent machines to work side by side on the shop floor for maximum efficiency moving from level 2 to level 3 would involve introducing intelligent automated machines, cobots and/or robots that enable individual employees to spend less time on tedious jobs and enabling them to take on more complex tasks.

Bio-bakery De Trog, an industrial craftmanships-bakery doubled its turnover and number of employees over a 5-year period. Every day more than 100 types of basic, locally sourced flower ingredients are being used through smart automation, delivering more than 300 different customer product types without jeopardizing the quality. Smart picking technologies (using Smart Glasses) strongly improved delivery reliability and the comfort of work for its employees.

In order to enable the company to adapt quickly to changing orders and customer request whilst at the same time keeping short throughput times, moving from level 3 to level 4 would require the company to manufacture to order small batch sizes and/or minimise changeover times between batches using an automatically planned manufacturing system. In this system the feedback of customers and suppliers is actively used to improve manufacturing processes and the company executes first experiments around data analytics and automated decision making through the use of Machine Learning and Artificial Intelligence.

Van Hoecke NV, a family owned SME of 200 employees, transformed from a local distributor of kitchen door-systems to a manufacturer of these products for the international market. The complete production set-up of Van Hoecke NV has been designed around small series (down to series of 1) and short throughput times (avg time needed from order to delivery is only 3 days).  Van Hoecke’s smart machines are fully digitally controlled using RFID-tags everywhere. Moreover, as the factory is only producing on a ‘make to order’ base, (intermediate) stock levels have been reduced to zero.

Van Hoecke NV, a family owned SME of 200 employees, transformed from a local distributor of kitchen door-systems to a manufacturer of these products for the international market. The complete production set-up of Van Hoecke NV has been designed around small series (down to series of 1) and short throughput times (avg time needed from order to delivery is only 3 days).  Van Hoecke’s smart machines are fully digitally controlled using RFID-tags everywhere. Moreover, as the factory is only producing on a ‘make to order’ base, (intermediate) stock levels have been reduced to zero.

First time right self-managed quality and process control systems enable companies to adapt quickly to changing orders and customer requests without jeopardizing quality levels and hence getting it right first time. Moving from maturity level 2 to level 3, would involve setting up a monitoring facility to control and predict product quality in the manufacturing processes.

Moving towards maturity level 3 in terms of real-time smart manufacturing KPI’s for monitoring, assessing and improving the company’s performance would require the use of such smart KPI’s to monitor and/or evaluate at regular intervals.

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