IEEE Instrumentation & Measurement - September 2023 - 6

Organization
context &
constraints
Do
ISO 9001:2015 - Section 7: Support
ISO 9001:2015 - Section 8: Operation
ISO 9001:2015 - Section 9:
Performance evaluation
Customer
satisfaction
Customer
specifications
Third-party
requirements
Act
Plan
Leadership
Check
Process status
Features of
products &
services
Fig. 1. The PDCA management model (Deming cycle) for quality-oriented organizations.
of product or services to requirements " (clause 7.1.5.1) [3].
More in general, the crucial role of measurement-related
tasks emerges directly or indirectly in at least other three sections
of the ISO 9001:2015 Standard, i.e., for process support
(Section 7), operation (Section 8) and performance evaluation
(Section 9). As far as the performance evaluation is
concerned, it is clearly stated in Section 9.1 that the organization
has to decide [3]:
◗ Which quantities need to be monitored and measured;
◗ The methods for monitoring, measuring, analyzing and
evaluating the collected data to ensure valid results;
◗ When and how often monitoring and measurement activities
as well as the processing of the collected data must
be performed.
Of course, an organization must evaluate the performance
and the effectiveness of the adopted Quality Management System
(QMS) by retaining appropriate documented information
as evidence of the results. To achieve this goal, first the organization
has to define the performance and acceptance
requirements on process inputs and outputs. Then, suitable
monitoring and measurement methods have to be chosen to
offer customers products/services under controlled conditions
and compliant with given quality or legal requirements.
Such general steps are critically important, especially in
Industry 4.0 and 5.0 scenarios, where the proper and reliable
fusion of large and heterogeneous sets of data collected
through networks of different kinds of sensors and/or from
distributed measurement devices is in the core of any smart
and sustainable manufacturing process. In fact, bad or missing
data due to sensor failure or degradation may not only lead
to wrong decisions based on poor or corrupted information
flows, but they may also disrupt the correct operation of automation
and control laws, thus drastically affecting the quality
of industrial outcomes and products.
Two interesting examples of Industry 4.0 mechatronic applications
where industrial metrology plays a central role
are described in [4]. In the former case study, a test bench
for the dynamic calibration of three-axis accelerometers in
6
the low frequency range is
proposed. This test bench
consists of a servo-motor
controlled by a programmable
logic controller (PLC)
driven by a high-accuracy
angular encoder. The servomotor
used to excite an
accelerometer under test is
driven by applying a given
motion law to stimulate specific
features of the sensor.
In this application, the mechatronic
model and control
parameters must be properly
optimized through
Design of Experiment
(DOE), Analysis of Variance
(ANOVA) or Response Surface Methodology (RSM), and they
should be constantly monitored to ensure adequate accuracy.
In the latter case study, a test bench for non-woven tissue
cutting is instrumented with different kinds of sensors
for predictive maintenance, i.e., to detect impending faults or
even to prevent failures at an early stage by using both physics-based
modeling and data-driven, machine-learning-based
approaches.
Of course, in both the aforementioned examples and whenever
some quantitative analysis supporting an industrial
process is needed, neither reliable process monitoring, nor
compliance to the wanted requirements is possible, unless sensors
and measurement instruments are properly calibrated. In
this regard, it is important to recall briefly the difference between
instrument calibration, verification and adjustment [5].
◗ Calibration consists of two steps. First, it establishes a relation
between one or more physical quantities (whose
values must be known with uncertainty provided by
appropriate measurement standards) and the corresponding
indication(s) returned by the instrument under
test. Then, this relation is used to return measurement
results from such indication(s).
◗ Verification includes all activities aimed at providing
objective evidence that a given item fulfills specified
requirements. For instance, in the specific case of measuring
equipment, instrument accuracy limits must safely
lie within given Max Permissible Error (MPE) limits. If
legal metrology aspects are involved, the verification of a
measuring system pertains to the examination, marking
and/or issuing of a compliance certificate.
◗ Finally, adjustment refers to a set of actions performed
on a piece of measuring equipment so that the indications
provided by the instrument correspond to known
values of the quantity or quantities to be measured. A
well-known example of instrument adjustment is the
auto-zero function (often improperly called self-calibration),
which is built-in into many pieces of electronic
equipment.
IEEE Instrumentation & Measurement Magazine
September 2023

IEEE Instrumentation & Measurement - September 2023

Table of Contents for the Digital Edition of IEEE Instrumentation & Measurement - September 2023

Contents
IEEE Instrumentation & Measurement - September 2023 - Cover1
IEEE Instrumentation & Measurement - September 2023 - Cover2
IEEE Instrumentation & Measurement - September 2023 - Contents
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