In order to remain competitive in today’s global
markets, manufacturing companies constantly need to adapt their production
structure and processes to suit customer needs.
The capture of production data and the reasons
and causes of faults and failures play an important role in a continuous process
Only those who know how and what is produced with
which system efficiency and quality are able detect losses and waste, define
optimization approaches and cost-reduction potential, guaranteeing optimum machine
utilization and productivity.
In the course of progressing globalization, an
increasing number of manufacturing companies recognize that production
management is of Eminent importance. Many standalone software
solutions of previous BDE/MDE systems are no longer able to meet today’s
requirements. MES systems, on the other hand, offer an integrated
solution for production management, connecting machine, product, master and
order data. With increasing automation in production plants, the requirements
for standardized interfaces to the production level in the MES environment also
With the support of an MES solution such as the iTAC.MES.Suite, all production data, processes, reasons for machine malfunctions and order data
are captured and documented and form the basis of the answers to the following questions:
How high is the actual productivity of the plant and the total plant efficiency (OEE)?
When, how often and why was there unscheduled machine downtime?
How high is the quality of the parts produced?
Which functional deficits occur?
Which potential cost-reduction and optimization methods are required?
How can the product be manufactured as efficiently as possible in hig quality and in large quantities?
How do production plants and lines directly compare directly?
The target for production management in the sense of contemporary
“Total Productive Management” (TPM) involves avoiding operational disturbances
of plants and the achievement “zero faults”, “zero defects” and “zero decline
in quality”, etc.
This approach results in clear requirements which integrated
MES systems are able to meet. Serialized product data and the machines and
materials used are captured, evaluated under Key Performance Indicators (KPIs)
and set into relation with each other. This data can be evaluated
effectively with different analysis methods.
As these KPIs are determined in quasi real time, they
can be used for direct and indirect production control and in avoiding losses and