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Standardisation of quality and reliability tests in the auto-parts industry: a structured approach concerning thermal systems



In the automotive industry, first-tier suppliers play an important role, as they often establish long-term partnerships with multiple car-makers for developing and supplying complete car modules. One of the conditions underlying these partnerships is the quality and reliability of car modules. To achieve it, car-makers generally require multiple tests, often on 100% of the parts subcontracted. The number of tests required can be very high, even for modules with a relatively low level of customisation. Also, the configuration of the tests can vary significantly from one car-maker to another, even for the same test typologies. The aim of this paper is to present a decision-support tool for the standardisation of quality and reliability tests, which uses some already available information on previous tests (e.g. about their effectiveness, cost and simplicity of execution) and involves experts both from the supplier's and car-makers' staff. Test standardisation is guided by a simple procedure based on two steps: (i) grouping the tests required by different car-makers into typologies of homologous tests, with a similar protection level in terms of product and quality reliability, and (ii) determining the most appropriate configuration for each test typology. The description of the methodology is based on a real case-study concerning a worldwide supplier of thermal systems.
Standardization of quality and reliability tests in the auto-parts industry: a
structured approach concerning thermal systems
Fiorenzo Franceschini1 and Domenico Maisano2
1; 2
Politecnico di Torino, DIGEP (Department of Management and Production Engineering),
Corso Duca degli Abruzzi 24, 10129, Torino (Italy)
In the automotive industry, first-tier suppliers play an important role, as they often establish long-
term partnerships with multiple car-makers, for developing and supplying complete car modules.
One of the conditions underlying these partnerships is the quality and reliability of car modules. To
achieve it, car-makers generally require multiple tests, often on 100% of the parts subcontracted.
The number of tests required can be very high, even for modules with a relatively low level of
customization. Also, the configuration of the tests can vary significantly from a car-maker to one
other, even for the same test typologies.
The aim of this paper is presenting a decision-support tool for the standardization of quality and
reliability tests, which uses some already available information on previous tests (e.g., about their
effectiveness, cost and simplicity of execution) and involves experts both from the supplier’s and
car-makers’ staff. Test standardization is guided by a simple procedure based on two steps: (i)
grouping the tests required by different car-makers into typologies of homologous tests, with a
similar protection level in terms of product and quality reliability, and (ii) determining the most
appropriate configuration for each test typology.
The description of the methodology is based on a real case-study concerning a worldwide supplier
of thermal systems.
Keywords: Quality and reliability test, Auto-parts, First-tier supplier, Car module, Standardization, Test
effectiveness, Thermal systems.
1. Introduction and problem definition
Since several decades, outsourcing plays a strategic role in the automotive industry (Franceschini et
al. 2003). Most of car-makers tend to build long-term partnership alliances with a relatively limited
number of first-tier suppliers, who are gaining more and more responsibility in the development of
entire car modules (e.g., engines, transmissions, braking systems, seats, tyres, etc.) and their
integration in the final product (Aláez-Aller and Longás-García 2010).
This tendency, accelerated by the recent socio-economic crisis, pushed suppliers in joining forces
either through mergers, acquisitions and joint ventures, so as to establish highly specialized and
efficient organizations serving a large number of car-makers (Schaede, 2010, Tsu-Ming, Fan-Yun &
Kai-I, 2013).
For simplifying the design and manufacturing stage without compromising product customization,
auto-parts suppliers generally develop a relatively small number of multifunctional
modules/platforms (Minhas et al. 2011). From the perspective of car-makers, ordering a complete
module reduces the number of parts to be outsourced and thus the time of assembly, quality control
cost, labour and administrative cost.
In the after-sales service, car-makers generally collect the so-called Voice of the Customer (VoC)
(Franceschini 2002; Sireli et al. 2007; Mavridou et al., 2013), to have an indication on the customer
satisfaction with the full “package” (i.e., the final product plus additional services, such as
maintenance program, roadside assistance, etc.). This information is strategic for car-makers
oriented at developing new products or improving the existing ones according to the real customer
requirements (van Driel and Dolfsma 2009). Sharing this information with suppliers, at least those
of the most “strategic” modules, is an important issue for consolidating partnerships. From the
perspective of suppliers, this constant flow of information is essential to guide the quality
improvement of the parts subcontracted, in accordance with the philosophy of “continuous
improvement” (Delbridge and Barton 2002 ).
Another condition to reinforce the partnership between suppliers and car-makers is the quality and
reliability of modules, which can have a very strong impact on the customer’s quality perception of
the final product. For example, a survey of an Italian car-maker showed that the majority of
customer complaints, relating to city-cars, concerned the performance of the heating-ventilating-
and-air-conditioning (HVAC) unit (Bassotto et al. 2005)! For achieving reliability, car-makers
generally require several tests, which should be carried out by suppliers often on 100% of the parts
supplied (Zhiqiang, Yuejun , Xiaole, 2013).
This paper will focus on a case-study concerning quality and reliability tests on thermal systems
(e.g., electric compressors, HVAC units, radiators, etc.) produced by an important worldwide
supplier, with a plant based in Northern Italy. For reasons of confidentiality, the company will be
kept anonymous and hereafter denominated with the acronym DTS. DTS supplies a large number of
car-makers, such as Fiat, General Motors, PSA, Renault, Volkswagen, etc., and, by tradition, gives
great importance to the product reliability.
It is worth noting that a scarcely debated issue in the scientific literature is that of the great variety
of tests required by car-makers to their suppliers. This variability is twofold:
1. In terms of test typologies. The total number of test typologies (i.e., groups of tests aimed at
testing the same function/attribute) can be very high, especially for parts subject to prolonged
and continuous use. In addition, similar tests can be considered as important by some car-makers
and neglected by others.
2. In terms of test configurations. For tests of the same typology, parameters (e.g., number of
cycles, temperature, pressure, etc.) can vary significantly from a car-maker to one other. The
practical implication is that tests of the same typology may be more or less effective, expensive
or simple to execute, depending on the configuration requested by car-makers.
The variety of test typologies and configurations can be large even for parts, such as thermal
systems, with a relatively low level of customization. This apparent paradox is explained by the fact
that car-makers generally develop their test practices individually. This generates a certain
“affection” for the practices in use and a consequent reluctance towards the introduction of possible
changes (Pil and MacDuffie 1999). Several existing techniques and procedures can be used for
assessing the capability of suppliers to (i) perform the tests imposed by a car-maker and (ii)
manufacture parts that satisfy these tests as much as possible; one of the most popular is the
Production Part Approval Process (PPAP), developed by the Automotive Industry Action Group
(AIAG) as part of the Advanced Product Quality Planning (APQP) manual (AIAG, 2006;
Franceschini et al., 2011). On the other hand, suppliers can hardly play an active role in reducing
test variety because of the lack of unified standards defining tests univocally and thoroughly. As a
result, managing quality and reliability tests may be complicated for multiple reasons:
Need for different types of test beds, some of which dedicated to just a few tests.
Flexibility of the operators, who must be able to switch from one configuration to one other (on
single or multiple test beds) without making mistakes.
Risk of biased conclusions about the actual reliability of the parts investigated, due to the fact
that different test configurations can be more or less effective; for example, a part passing the
test by one car-maker could not pass that by another one.
Operating costs likely to grow.
The previous considerations highlight the need for reducing the variety of tests in a rational way.
The objective of this paper is the introduction of a simple standardization procedure based on two
main steps: (i) grouping the tests required by different car-makers into typologies of homologous
tests, with a similar protection level in terms of product reliability, and (ii) determining the most
reasonable and appropriate configuration for each test typology.
The proposed procedure uses the results of previous tests and the opinion of experts – i.e., engineers
and/or technicians – both from the supplier’s and the car-makers’ staff.
The remainder of this paper is organized in two sections. Sect. 2 illustrates in detail the
standardization procedure, providing an application example to reliability testing on radiators
produced by DTS. The concluding section summarizes the original contribution of the manuscript
and discusses the advantages and limitations of the proposed procedure.
2. Methodology
Tab. 1 summarizes the phases of the proposed procedure, which are described individually in the
following subsections. The description is based on a case-study concerning tests on radiators
supplied by DTS to four worldwide car-makers (CM1 to CM4). For reasons of confidentiality, car-
makers are kept anonymous.
Phase denomination Input Output Subjects involved
2.1 Identification of test typologies Technical specifications
concerning the tests required
by the car-makers
List of the test typologies, with
their individual configurations
A team of experts on
reliability tests from DTS
2.2 Determination of the importance
level of test typologies
Questionnaires submitted to
Judgements defined on a
5-level ordinal scale
Experts on reliability tests
both from the staff of
DTS and that of each car-
2.3 Comparison of the alternative
configurations (for each individual
test typology)
- - -
2.3.1 Definition of judgements
relating to each configuration
Results of previous reliability
tests and questionnaires
submitted to experts
Judgements defined on 5-level
ordinal scales (concerning
effectiveness, cost, simplicity
of execution)
A team of experts on
reliability tests from DTS
2.3.2 Selection of the most suitable
Judgements resulting from
phases 2.2 e 2.3.1
Selection of a configuration for
each test typology
A team of experts on
reliability tests from DTS
Tab. 1. Typical phases of the test standardization procedure, specifying input/output data and subjects involved.
2.1 Identification of test typologies
One of the most delicate phases of the procedure is the classification of the tests imposed by various
car-makers into groups of homologous tests. Consistently with the definition of reliability, i.e., “the
ability of a system or component to maintain its functions/attributes under stated conditions for a
specified period of time” (O’Connor 2002), homologous tests should be focused at testing the
maintenance of similar functions/attributes (e.g., corrosion resistance, sealing, etc.). Unfortunately,
this classification is complicated by the fact that there is no standard to define the set of
functions/attributes of a generic system uniquely. We take the liberty to clarify this issue through a
similarity between the concept of measurement and that of reliability test.
A measurement is an operation for estimating an attribute of a real entity (e.g., the length of an
object), using an appropriate instrument (e.g., a tape, a calliper, a laser interferometer or an echo
sounder). Results of measurements obtained by different instruments can be compared since they
are linked to the same reference unit (e.g., in the case of length measurements, the meter). This link
originates from the instrument calibration process, which establishes a connection between the
measurement result and the reference unit by an unbroken metrological traceability chain
(JCM200:2012 2012). Of course, the results of measurements performed using different instruments
may differ in several aspects, such as accuracy, cost, simplicity of execution, etc..
On the other hand, reliability tests can be viewed as special measurements for assessing the ability
of a component to maintain a certain function/attribute over time. Even considering the same
function/attribute, there can be different instruments (test beds) and procedures (configurations of
test parameters) to test it, as evidenced by the variety of tests suggested by different car-makers.
Unfortunately, the results of tests performed with different instruments and/or procedures are not
easy to compare for at least two reasons: (i) the difficulty in identifying the functions/attributes of a
system uniquely, and (ii) the lack of standard references for establishing the conditions in which
evaluating the maintenance of these functions/attributes.
The large variety of tests imposed by various car-makers is also reflected by their denominations: in
most cases, car-makers use acronyms or reference numbers referred to internal procedures.
A possible way to overcome these limitations (at least partially), allowing comparisons among tests
suggested by different car-makers, is to create typologies of homologous tests. This activity can be
carried out by a team of experts, consisting of engineers and/or technicians with a deep experience
and knowledge of the tests of interest.
Tests of the same typology will differ in several aspects, such as effectiveness – defined as the
ability of the test to reveal the maintenance of a certain function/attribute, in a realistic operational
context – cost, simplicity of execution, etc.. We are aware that the definition of test typologies is a
subjective operation. However, the fact that it is carried out by a team of multiple experts represents
a partial guarantee for obtaining reasonable results.
Tab. 2 lists the test typologies defined by the team of experts from DTS staff. It can be seen that test
typologies are variegated; about half of them are required by the majority of car-makers but only 9
out of 28 are shared by all of them. Also, there are several tests required by few or even individual
car-makers. Those requested by unique car-makers (highlighted in gray in Tab. 2) were not taken
into account.
Ref. no. Test typology denomination CM1CM2 CM3 CM4
T1 Bursting test    
T2 Drain packing    
T3 Draincock    
T4 External corrosion (salt spray)    
T5 External corrosion (severe wastewater analysis)    
T6 Fluid cooler heat exchange    
T7 Functional characteristics    
T8 General characteristics    
T9 Internal cleanliness    
T10 Internal corrosion    
T11 Leak    
T12 Long life coolant resistance    
T13 Low Temperature    
T14 Performance measurement    
T15 Phys./Chem./ Environm./Mech.    
T16 Pollution    
T17 Pressure cap wear    
T18 Pressure cycle durability    
T19 Pressure resistance    
T20 Resistance to fastening dowels    
T21 Resistance to fluid attack    
T22 Resistance to gravelling    
T23 Resistance to painting    
T24 Rubber seal    
T25 Temperature endurance    
T26 Thermal cycle durability    
T27 Vacuum    
T28 Vibration durability    
Tab. 2. List of the test typologies concerning radiators manufactured by DTS, sorted alphabetically by their
denomination. Test typologies required and non-required by each of the car-makers (CM1 to CM4) are
respectively marked by the symbols “” and “”. The test typologies highlighted in grey are required by unique
car-makers and therefore will not be taken into account in the rest of the analysis.
2.2 Determination of the importance level of test typologies
The level of importance of a test typology depends on the negative effects, which may originate
from the loss of the function/attribute investigated. This judgement may change from a car-maker to
one other. For example, test typology “T11–Leak” is regarded as very important by the totality of the
car-makers, because leakage from the radiator can rapidly lead to compromising its main function
of cooling the car engine. Instead, some car-makers consider the typology “T10–Internal corrosion”
as important, while others do not.
This judgement was collected by questionnaires submitted to experts in reliability tests, both from
the DTS’ and car-makers’ staff. Experts from the car-makers were engineers and/or technicians
dealing with DTS for technical issues about the tests of interest. Judgments were collected for DTS
and each of the four car-makers separately.
To make judgments as simple as possible, it was adopted a 5-level ordinal scale (see the second
column in Tab. 3). The category N/A (not applicable) was assigned to car-makers not requiring the
test typology of interest.
Level Importance
(of a test typology)
(of a configuration)
(of a configuration)
(of a configuration)
1 Not at all important Not at all effective Very high cost Not at all simple
2 Low importance Low effectiveness High cost Low simplicity
3 Medium importance Medium effectiveness Medium cost Medium simplicity
4 High importance High effectiveness Low cost High simplicity
5 Very high importance Very high effectiveness Very low cost Very high simplicity
N/A Not applicable Not applicable Not applicable Not applicable
Tab. 3. Definition of the 5-level scales used for evaluating (i) the importance of a test typology and (ii) the
effectiveness, cost and simplicity of execution of the relevant test configurations.
In order to facilitate the formulation of judgments, we provided respondents with the results of a
previous Failure Mode, Effects, and Criticality Analysis – FMECA (Bouti and Kadi 1994) on the
radiator, which identified and prioritized the main failures.
It is reasonable to assume that the major test typologies are those investigating the maintenance of
functions/attributes potentially affected by the most critical failures. Tab. 4 illustrates the results of
the questionnaires for each test typology. The most important typologies at global level are those
requested by a large number of car-makers and those with relatively high importance judgements.
For each test typology, it is possible to determine the median1 level of importance:
)( i
, (1)
being Ii the importance levels assigned by experts from DTS and each of the car-makers (if
applicable). Precisely, subscript
ADTSi , where
4321 CM,CM,CM,CMA indicates
groups of experts from the subset of car-makers requiring the test typology of interest. E.g., the test
typology T1 is required by CM3 and CM4, but not by CM1 and CM2, therefore A={CM3, CM4}.
ref. no.
T1 4 N/A N/A 5 4 4
T3 1 1 2 1 N/A 1
T4 3 5 3 4 4 4
T5 3 4 4 5 5 4
T9 2 1 1 3 1 1
T10 1 4 3 1 1 1
T11 4 4 5 5 5 5
T13 3 2 1 2 N/A 2
T14 5 5 5 3 2 5
T15 1 N/A N/A 1 1 1
T18 5 5 5 4 4 5
T23 3 N/A N/A 2 4 3
T26 5 4 5 5 5 5
T27 4 5 N/A N/A 3 4
T28 3 5 5 5 2 5
Tab. 4. Judgements of experts from DTS and four car-makers (CM1 to CM4) on the importance of the test
typologies in Tab. 2.
is the median the importance values relating to each test typology.
1 Using the average value as a central tendency indicator may be inappropriate since Ii values are defined on an ordinal
scale (Stevens 1946).
will be used in the next stages of the procedure (see the last column of Tab. 4). For simplicity, it
was assumed that judgements by the groups of experts from DTS and each of the car-makers have
the same relevance.
It can be noticed that, even for tests of the same typology, there can be significant differences
between the judgements by different respondents. This is probably the result of their specific
experience on previous tests.
2.3 Comparison of the alternative configurations
2.3.1 Definition of judgments relating to each configuration
In this phase, the attention is focussed on the configurations imposed by different car-makers for
each of the test typologies selected in Sect. 2.1. For the purpose of example, Tab. 5 reports the
configurations concerning to the test typologies “T1–Bursting test” and “T26–Thermal cycle
Test typ. CM1 CM2CM3CM4
T1 N/A N/A Fill radiator with test fluid;
Increase pressure at
4bar/min, up to 3.5bar;
Hold this pressure for 30s.
Pressure (1.5*inlet pressure);
Increase pressure at 0.1bar/s, up to
Hold this pressure for 300s;
Ambient temperature: 23±5 °C.
T26 No. of cycles: 1000;
Coolant temperature: from 0°C
to 100±2°C;
Pressure: 130±10kPa.
No. of cycles: 7000;
50% water 50% coolant as
Coolant temperature: from
20 °C (30 s max) to 90 °C
(2 min) and to 20°C (2 min)
with flow rate 40 l/min.
No. of cycles: 1000;
Cycle rate: 7 cycles/h;
Coolant temperature: from
-30 °C to 100 °C;
Pressure: 1.3 bar.
No. of cycles: 2500;
Pre-conditioning: 2 h at 20 °C;
Ambient temperature: 23±5 °C;
High temperature of coolant:
113 °C;
Low temperature of coolant: 23 °C;
Switch duration between high and
low temperature phase: 5 s;
Tab. 5. Configurations of the test parameters for test typologies “T1–Bursting test” and “T26–Thermal cycle
durability”, from the perspective of four car-makers (CM1 to CM4).
For each of these configurations, different aspects were investigated. The first one is the test’s level
of effectiveness in detecting possible abnormalities of the part in maintaining its functions/attributes.
The survey was carried out by submitting questionnaires to a team of DTS experts, already involved
in the activities described in Sects. 2.1 and 2.2.
Again, judgements were defined on a 5-level ordinal scale (see the third column in Tab. 3). In
general, it was assumed that the most effective tests tend to be severe/conservative, generating a
significant amount of “false positives”, i.e., parts that did not pass the test, while being functionally
acceptable (in statistical terms, a greater type-I error). Therefore, very high levels of effectiveness
are justified only for test typologies of high importance, for which it can be reasonable to minimize
the probability of “false negatives” (in statistical terms, the type-II error), i.e., parts with
deteriorated function(s)/attribute(s), which passed the test. Tab. 6 shows the resulting judgements
(see the column “Eff”, for each car-maker).
Respondents were subsequently asked to judge the level of cost and simplicity of execution of each
configuration. Cost, which generally depends on test time and hourly cost of equipment/operator(s),
is quite simple to estimate. On the other hand, simplicity – which may depend on the complexity of
test set-up, risk of human error, operators’ degree of familiarity with the equipment, etc. – is more
difficult to quantify. These judgements were defined on two 5-level scales (see the fourth and fifth
column in Tab. 3). The scale related to cost is “reversed”, so that low and high levels have a
negative and positive connotation respectively. Tab. 6 shows the resulting judgements (see the
columns “Cost” and “Simpl” for each car-maker).
~ CM1
Ref. No. Eff Cost Simpl Eff Cost Simpl Eff Cost Simpl Eff Cost Simpl config.
T1 4 N/A N/A N/A N/A N/A N/A 3 2 2 5 3 2 CM4
T3 1 3 1 3 2 2 2 1 3 3 N/A N/A N/A CM3
T4 4 3 2 2 4 4 2 5 4 2 5 2 2 CM2
T5 4 4 1 2 5 2 1 5 1 2 4 1 1 CM1
T9 1 3 2 1 1 1 3 1 1 1 3 3 1 CM2
T10 1 4 5 5 2 5 5 1 3 4 2 5 5 CM3
T11 5 3 4 3 5 4 4 5 5 5 4 3 3 CM3
T13 2 1 2 1 1 1 1 1 1 2 N/A N/A N/A CM2
T14 5 4 4 2 2 3 2 3 2 4 3 2 4 CM1
T15 1 N/A N/A N/A N/A N/A N/A 1 3 4 3 2 1 CM3
T18 5 4 5 5 3 4 5 4 5 3 4 5 4 CM1
T23 3 N/A N/A N/A N/A N/A N/A 5 2 3 4 1 1 CM4
T26 5 3 3 4 5 4 5 4 4 3 5 3 5 CM2
T27 4 2 1 1 N/A N/A N/A N/A N/A N/A 5 1 1 CM4
T28 5 4 1 1 4 1 2 4 2 2 3 1 1 CM3
(1) In this case, Effi<I
~for all the alternative configurations; as a result, Eq. 2 can not be applied. The selected configuration is the one
with max(Effi).
Tab. 6. Judgments of experts from DTS about the degree of effectiveness (Eff), cost and simplicity of execution
(Simpl) of the test configurations proposed by any of the car-makers (CM1 to CM4). The last column shows the
configuration selected according to the procedure described in Sect. 2.3.2.
2.3.2 Selection of the most suitable configuration
Among the possible configurations, the “best” is selected according to the procedure illustrated in
the flowchart in Fig. 1.
As shown, in the case there are two (or more) configurations that satisfy the condition
min(Effi | Effi
), (2)
being iA, i.e. the subset of car-makers requiring the test typology of interest, the selection
continues by applying a lexicographic order based on cost and simplicity of execution. In the
unlikely event of a further tie, the final decision would be determined manually by the team of
Identify the configuration(s) with
Collection of judgements concerning the
alternative test configurations
Is the solution univocal (i.e., no ties)?
YES Is the solution univocal (i.e., no ties)?
Among the joint winners, identify
the one(s) with max(Simpl
NO YES Is the solution univocal (i.e., no ties)?
Manual choice of the best
configuration by the team of experts
Among the joint winners, identify
the one(s) with max(Cost
Fig. 1. Flowchart depicting the procedure for selecting the “best” configuration, for a certain test typology.
The last column in Tab. 5 reports the configurations selected applying the previous procedure.
For the purpose of example, as regards T9, two are the configurations satisfying Eq. 2: CM2 and
CM3. Since these two alternatives have the same cost level (i.e., 1), the selection is determined by
simplicity of execution, which is higher for CM2 (i.e., 3) with respect to CM3 (i.e., 1).
The logic of selection seen above is based on several assumptions:
The best configuration is not defined “from scratch”, instead it is selected among those imposed
by the car-makers. Defining the parameters of a test is actually a very delicate operation because
of the multiplicity of factors (e.g. as regards radiator: number of cycles, temperature, pressure,
composition of coolant, etc.), which may affect its effectiveness. These factors and their possible
interactions should be examined rigorously by experimental plans (Box et al. 1978). It was
assumed that the test configurations were defined by the car-makers following this approach.
It was assumed that test effectiveness and severity, i.e., the probability to generate “false
positives”, go hand in hand. The fact that the selected configuration should have a level of
effectiveness as close as possible to that of
prevents from selecting (i) tests that are too severe
with respect to their relatively low importance, or (ii) tests that are not very effective, despite
their relatively high importance. The authors are aware that, in some cases, this assumption may
not be realistic. For example, there could exist very effective configurations with relatively low
incidence of “false positives”. When, on the basis of its experience, the team of expert feels that
this hypothesis should be relaxed, one could select the configuration satisfying the condition:
max(Effi). (3)
Also, Eq. 3 could be used when there is no configuration satisfying Eq. 2, because Effi <
Ai (see tests T13, T14, T18 and T28 in Tab. 6).
Among the three types of judgements (effectiveness, cost, simplicity) related to the
configurations, it was implicitly assumed the ordering Eff > Cost > Simpl (symbol “>” means
“preferred to”). However, the technique based on lexicographic ordering could be replaced by
more complex techniques, such as Multi-Criteria Decision-Making (MCDM) methods
(Franceschini et al. 2007; Köksalan et al. 2011).
3. Final remarks
This work focused on the problem of the standardization of reliability tests for auto-parts suppliers.
This problem originates from (at least) two reasons: (i) in general there are no unified standards
defining exhaustive and univocal sets of tests, and (ii) any car-maker requires a set of tests, with ad
hoc configurations deriving from their specific experience and work practices.
The proposed procedure is a first attempt to address this problem in a simple and economic way. A
more elegant and sophisticated approach would be that of designing new optimal configurations, in
terms of effectiveness, through rigorous design of experiments (DoE). Unfortunately, the price to
pay would be too high because of the large number of experiments required. On the contrary, the
proposed technique exploits a large amount of information already available (i.e., results of
previous tests) and the expertise of engineers and/or technicians from suppliers and car-makers.
The procedure was applied in DTS on a number of thermal systems, such as radiator, HTVC, heater
core, etc., focussing on the test configurations imposed by several worldwide car-makers. The
example presented in this paper illustrated the philosophy behind the procedure.
Thanks to its simplicity and low cost, the procedure was judged by DTS staff as very useful and
easy to implement. For this reason, it will be extended to other components manufactured by the
company. The proposed methodology can be considered as a decision-support tool for rationalizing
the management of reliability tests for auto-parts suppliers, which is complementary to other
procedures, such as the AIAG’s APQP/PPAP (AIAG, 2006).
The proposed approach has some limitations, summarized as follows:
Test standardization is internal with respect to a specific supplier, since it depends on the degree
of expertise of engineers/technicians, the information regarding previous tests, the available
equipment (test beds) and the variety of tests imposed by car-makers. As a consequence, the
application of the procedure to different suppliers could lead to different results, even
considering homologous parts.
Several phases of the procedure are subjective, such as the interpretation of the results of
previous tests or the formulation of judgments. To avoid disputes, these phases should be carried
out in a transparent manner, involving technical staff with a certain expertise on reliability tests,
both from suppliers and car-makers.
The procedure can be applied to auto-parts with a relatively low degree of customization, where
comparing tests related to similar product models is not hasty.
Standardized tests may be rejected by some car-makers, who are “attached” to their
configurations. However, the results of the proposed procedure may be used for persuading the
most reluctant car-makers to accept standardized tests, as they will probably be more effective,
cheaper and simpler than other ones.
Authors gratefully acknowledge the contribution of Giridharan Sundar and the company staff of DTS, in
developing the proposed methodology.
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... The new version of the quality management standard ISO 9001:2015 emphasizes the risk-based thinking for product quality management; as such, risk-based thinking becomes an inevitable trend of quality analysis [7,8]. Therefore, risk-based thinking is considered to manage the decline of assembly system health, and the concept of assembly system health risk is proposed. ...
... Therefore, modeling the quantitative relationship between product KRC variations and the assembly system health risk is the most important part for assessing the assembly system health. Thornton [7,8] proposed the VRM model for the risk caused by process variation. On this basis, a health risk assessment model for the product assembly system is proposed. ...
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Assembly quality is the barometer of assembly system health, and a healthy assembly system is an important physical guarantee for producing reliable products. Therefore, for ensuring the high reliability of products, the operational data of the assembly system should be analyzed to manage health states. Therefore, based on the operational data of the assembly system collected by intelligent sensors, from the perspective of quality control based on risk thinking, a risk-oriented health assessment method and predictive maintenance strategy for managing assembly system health are proposed. First, considering the loss of product reliability, the concept of assembly system health risk is proposed, and the risk formation mechanism is expounded. Second, the process variation data of key reliability characteristics (KRCs) collected by different sensors are used to measure and assess the health risk of the running assembly system to evaluate the health state. Third, the assembly system health risk is used as the maintenance threshold, the predictive maintenance decision model is established, and the optimal maintenance strategy is determined through stepwise optimization. Finally, the case study verifies the effectiveness and superiority of the proposed method. Results show that the proposed method saves 37.40% in costs compared with the traditional method.
... Available elaborates are mainly focused on the system recognition of the relations between the parts manufacturer and cars manufacturer [28], management of the quality of suppliers [17], costs of the quality of suppliers [24], methods and devices used for the management of the quality in the automotive industry [22], systems, standards conditioning of the implementation of quality management in the automotive industry [6], effectiveness of the quality management systems [19], management of supplies chains [7] or applications of the quality management systems by suppliers [1]. As it comes to the precise issue concerning the quality of parts, in the analysed elaborates, it covered the control at the produc-tion stage and directly after it [14], standardization of the quality tests including the reliability for the parts manufacturers [4], quality challenges and the outline of directions of quality improvement for parts manufacturers [20], quality of the parts in the context of the calling actions [8] or the issues connected with logistics and packaging of automotive parts [29]. ...
... 3. The elaborated metamodel shows that the classifications of variables into quality criteria of the selection of spare parts for two multidimensional exploratory techniques differ, although there are some common elements such as utility criterion (covering 6 variables) and a considerable part of the marketing criterion (4 variables: in cluster analysis there are 2 additional variables). 4. In factor analysis we distinguished separate factors describing the availability and costs of the parts. ...
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The aim of the paper was (1) to compare cluster analysis and factor analysis applied in the classification of variables into quality criteria of spare parts selection for passenger cars and (2) to create a metamodel taking into account the similarities and differences between the results of the carried out analyses. To collect empirical data, a survey questionnaire was used. It was built on the basis of literature overview concerning quality management. Data was processed with the use of multi-dimensional exploratory techniques: cluster analysis and factor analysis. A theoretical implication is a proposed metamodel, which joins the results of both cluster and factor analysis. A practical implication is a possibility of taking an advantage on the obtained results when planning, designing, manufacturing, distributing, selecting and selling spare parts for passenger cars. Paper contribution is the use of exploratory data analysis techniques in the research area and the proposal of the metamodel formalizing quality criteria of spare parts selection for passenger cars. The research showed, that classifications of variables obtained with the use of two multi-dimensional exploitation techniques are different although there are distinct common elements. When using cluster analysis, the following clusters were identified: marketing, economy and utility one (arranged in accordance with the order of linking). While when using factor analysis, the following factors were discovered: utility, marketing, availability and cost factor (arranged in descending way in accordance with the explained variance).
... This situation implies that reliability assurance should be coordinated with traditional manufacturing quality analysis to mitigate the risks caused by potential product failures built in the manufacturing process (He, Zhu, He, Gu, & Cui, 2017). Therefore, strengthening the consideration of product reliability improvement in various manufacturing decision-making activities is gradually gaining manufacturers' attention (Fiorenzo & Domenico, 2015). ...
Superior manufacturing quality is prerequisite to continuously produce reliable products, and the proactive product reliability assurance is always a crucial routine task for manufacturing. Therefore, this paper presents a reliability-oriented optimization model for joint preventive maintenance (PM) and process quality control with time-between-events (TBE) control chart, where the impact of manufacturing process on product final reliability is considered to reduce the product reliability degradation originating from latent manufacturing defects. Firstly, as the foundation of reliability-oriented control, the product reliability degradation mechanism in manufacturing stage is analyzed, and the process variations of product critical-to-reliability characteristics and internal defects are considered to model the product actual reliability. On this basis, periodical PM and TBE chart are jointly applied to enhance machine performance and improve manufacturing process quality to reduce potential reliability degradation, and a three-scenario model is proposed. Then, to evaluate the performance of the integrated model, the occurrence probability, expected reliability degradation, average operational cost, and cycle time of each scenario are analyzed, and the joint policy is optimized to minimize the expected reliability degradation of batch products within a limited cost range. Finally, a case study is presented to verify the performance of the developed model by comparing it with a pure planned maintenance policy, and a sensitivity analysis is conducted to analyze the impacts of model parameters.
... Even more, there are no test standards available with appropriate pass/fail criteria for the (key) components and/or SSL products [1]. Relationships with material and component suppliers need to be tightened, as is the case in the automotive industry [14], in order to share the responsibility for the product quality and reliability. In other words: a huge mind-set change is needed in reliability to make the market introduction of SSL application a big success. ...
Human civilization revolves around artificial light. Since its earliest incarnation as firelight to its most recent as electric light, artificial light is at the core of our existence. It has freed us from the temporal and spatial constraints of daylight by allowing us to function equally well night and day, indoors and outdoors. It evolved from open fire, candles, carbon arc lamp, incandescent lamp, fluorescent lamp to what is now on our door step: solid state lighting (SSL). SSL refers to a type of lighting that uses semiconductor light-emitting diodes (LEDs), organic or polymer light-emitting diodes (OLED/PLED) as sources of illumination rather than electrical filaments, plasma (used in arc lamps such as fluorescent lamps), or gas. SSL applications are now at the doorstep of massive market entry into our offices and homes. This penetration is mainly due to the promise of an increased reliability with an energy saving opportunity: a low cost reliable solution. An SSL system is composed of a LED engine with a micro-electronics driver(s), integrated in a housing that also provides the optical, sensing and other functions. Knowledge of (system) reliability is crucial for not only the business success of the future SSL applications, but also solving many associated scientific challenges. In practice, a malfunction of the system might be induced by the failure and/or degradation of the subsystems/interfaces. This paper will address the items to ensure high reliability of SSL systems by describing LED degradation from a component and a system perspective.
... Integrating different management systems in a manufacturing enterprise is a trend in the newly released ISO9001 standard for the quality management system (Chad, 2015;Rameshwar, Angappa, Stephen, Samuel, & Thanos, 2015;Fiorenzo & Domenico, 2015), which shows the direction for enhancing the reliability assurance in production. Therefore, to generate a reliable product with acceptable cost of poor quality, reliability assurance approaches should be integrated with quality control systems (Patrick & Andre, 2012). ...
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Reliability assurance is a series of activities that ensure that the product reliability requirements be realised in a product life cycle. However, as reliability assurance activities are usually only implemented in design and usage, the integration of reliability assurance with quality control in production has not attracted the attention it deserved, thereby hindering production performance improvement to satisfy increasingly stringent customer requirements. To this end, this paper proposes a reliability-oriented quality control framework to integrate quality control and reliability assurance in production according to the principles of total quality management (TQM). Firstly, from the integrated quality and reliability assurance perspective, the RQR chain is proposed to represent the bidirectional relationships among the three basic management objects in a production process, namely,manufacturing system reliability (R), manufacturing process quality (Q), and the produced product reliability (R). Secondly, a reliability-oriented quality control framework for the production process based on the RQR chain is presented to provide the control clue for a manufacturing enterprise. Thirdly, the validity of the proposed approach is verified in a vehicle engine manufacturing enterprise of China.The proposed RQR chain as a decision-support model for TQM is eventually proven effective in promoting the integration of quality control and reliability assurance in production.
Aiming at the problem of product processing quality management in automobile manufacturing supply chain, the concepts of automobile manufacturing supply chain and medium auto parts enterprise are put forward, the theory of product life cycle and relationship life cycle is introduced, and the automobile manufacturing supply chain is divided into product processing preparation stage, product sample performance evaluation stage and product production and operation stage. The cooperation model of the medium enterprise in the automotive manufacturing supply chain is constructed, the management characteristics and key influencing factors of the medium auto parts enterprises in the three stages of the automotive manufacturing supply chain are analyzed, and from the perspective of the supply chain, the product processing quality management demand model of the medium enterprise is established. Taking a new product manufacturing of an auto parts enterprise in China as an example, the practicability and rationality of the proposed concept and model are verified.
In high-quality manufacturing processes, the yield is no more the only issue, and the quality control approach that also considers the product’s actual performance gradually becomes the focus. Reliability is a critical dimension of quality, and its degradation in usage is always determined by the manufacturing quality. To mitigate the degradation of reliability, this article presents a product reliability–oriented optimization design of the time-between-events control chart system, where the quantitative impact of process quality on the product reliability is analyzed. First, critical-to-reliability process parameters are identified, and a product reliability degradation model is proposed considering the effect of process variations and defects. Second, the observed event and the used statistics are determined to prearrange the time-between-events chart system. Third, all individual time-between-events charts are systematically optimized to minimize the expected batch product reliability degradation caused by potential process shifts, where the cost and statistical performance are considered as constraints. The result of the case study shows that the proposed design can reduce 27.02% of batch product reliability degradation due to manufacturing process quality, and this model can also save the operating cost on the basis of attaining minimum reliability degradation in certain situations.
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A world that is changing faster and faster forces companies to a continuous performance monitoring. Indicators give the impression to be the real engine of organizations or even the economy at large. But performance indicators are not simple observation tools. They can have a deep "normative" effect, which can modify organizational behaviour and influence key decisions. Companies are what they measure! The selection of good performance indicators is not an easy process. This monograph focuses on the designing of a Performance Measurement System (PMS), knowing that "magic rules" to identify them do not exist. Some indicators seem right and easy to measure, but have subtle, counter-productive consequences. Other indicators are more difficult to measure, but focus the enterprise on those decisions and actions that are critical to success. This book suggests how to identify indicators that achieve a balance in these effects and enhance long-term profitability.
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Multinational companies are a conduit by which superior organizing principles can be transferred across national, institutional, and cultural environments. However, for such transplantation efforts to be successful, the companies face the challenge of adapting their practices and principles to the requirements of local environments. In the process they risk losing the performance benefits from those practices. In this paper we study the North American transplant production facilities of Japanese automobile producers—companies known for their ability to achieve superior labor productivity and quality in their manufacturing plants, along with high levels of product variety—for insight into how the practices associated with superior performance (including work systems, technology choices, and supplier relations) can be implemented outside of Japan. By comparing the Japanese transplants with automobile plants in Japan, and Big 3 plants in North America, we show that the extent of transfer varies by type of practice. Furthermore, we find that plants can shape and alter their external environment, and can also buffer themselves from it. Despite these modifications, we find that the transplants are able to achieve productivity and quality levels similar to plants in Japan.
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Purpose – The purpose of this paper is to disentangle and elaborate on the constitutive elements of the concept of path dependence (initial conditions and lock-in) for a concerted and in-depth application to the study of organizational change. Design/methodology/approach – The approach takes the form of a combination of a longitudinal and a comparative case-study, based on secondary literature. Findings – External initial conditions acted less as “imprinting” forces than is suggested in the literature on the genesis of the Toyota production system (TPS); a firm-specific philosophy in combination with a critical sequence of events mainly shaped and locked-in TPS. Research limitations/implications – The empirical sources are limited to publications in English, so relevant factors explaining the path taken may not all have been included. The importance of a salient meta-routine might be firm-specific. Practical implications – The study contributes to understanding the factors underlying corporate performance by a critical re-examination of a much heralded production system (TPS). Originality/value – The paper highlights the use of the concept of meta-routines to connect the core elements of path dependence, that is, sensitivity to initial conditions and lock-in mechanisms.
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One prominent feature of Japanese automobile manufacturing in the postwar period was a system of sourcing parts from closely affiliated smaller firms in long-term, stable relations. Changes in the global automobile industry have made that system too expensive. Increasing competitive pressures resulting from global excess capacity in the early 2000s and have forced a transformation in the business model of the automotive industry. Modulization and a switch to "global best sourcing" for standard parts have turned the previous logic of Japanese subcontracting on its head, as first-tier suppliers become even closer partners of large assemblers, while small firms become replaceable. Mergers and joint ventures have changed the structure of Japan's auto part industry, resulting in larger firms that compete globally. Undergoing a transformation toward cost-cutting and increased technological capabilities in the late 1990s and early 2000s has afforded these firms a fortuitous head start in preparing for the global auto crisis of 2008/09, which is threatening to wipe out smaller parts markers around the globe.
Multiple Criteria Decision Making (MCDM) is all about making choices in the presence of multiple conflicting criteria. MCDM has become one of the most important and fastest growing subfields of Operations Research/Management Science. As modern MCDM started to emerge about 50 years ago, it is now a good time to take stock of developments. This book aims to present an informal, nontechnical history of MCDM, supplemented with many pictures. It covers the major developments in MCDM, from early history until now. It also covers fascinating discoveries by Nobel Laureates and other prominent scholars.The book begins with the early history of MCDM, which covers the roots of MCDM through the 1960s. It proceeds to give a decade-by-decade account of major developments in the field starting from the 1970s until now. Written in a simple and accessible manner, this book will be of interest to students, academics, and professionals in the field of decision sciences. © 2011 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
The Failure Mode and Effects Analysis (FMEA) documents single failures of a system, by identifying the failure modes, and the causes and effects of each potential failure mode on system service and defining appropriate detection procedures and corrective actions. When extended by Criticality Analysis procedure (CA) for failure modes classification, it is known as Failure Mode Effects and Criticality Analysis (FMECA). The present paper presents a literature review of FME(C)A, covering the following aspects: description and review of the basic principles of FME(C)A, types, enhancement of the method, automation and available computer codes, combination with other techniques and specific applications. We conclude with a discussion of various issues raised as a result of the review.
This historical note is based on a plenary talk ‘A History of Early Developments in Multiple Criteria Decision Making’, presented by Stanley Zionts at the 21st International Conference on Multiple Criteria Decision Making held in Jyväskylä, Finland, June 2011. It draws heavily on our book, Multiple Criteria Decision Making: From Early History to the 21st Century, published by World Scientific, Singapore, 2011. Copyright © 2013 John Wiley & Sons, Ltd.
Since most manufacturers promote ISO/TS16949 quality system certification process through the help of external counsellors, this study focuses upon the auditors of ISO/TS 16949 as the primary objects of the research, in contrast to previous studies targeting certified manufacturers. Collecting data through questionnaire surveys, this study first utilises Kano's model to discover the main factors identified as potential improvements by ISO/TS 16949, then uses fuzzy analytic hierarchy process to rank the importance of these factors, and finally introduces the quality function deployment (QFD) relation matrix to discuss the key factors to a successful implementation of ISO/TS 16949 certification. The results show that two remarkable improvement factors of enterprises promoting ISO/TS 16949 certification lie in identifying internal customers to meet the requirements to complete the product, and identifying production and service supply processes to meet the requirements. Results acquired from QFD further show that customer information collection, internal auditing capability, and statistical analysis capability are the necessary technical demands to achieve these essential improvements. The results can help enterprises effectively allocate resources to implement the quality system of ISO/TS 16949.
A joint model for integrating run-based preventive maintenance (PM) into the capacitated lot sizing problem (CLSP) is proposed, in which the production system is subject to deterioration with usage and PM operations are implemented to restore the system. In this model, both production and PM operations are restricted by the system's maximum capacity, and the system reliability has to be maintained above a threshold value throughout the planning horizon. By linearisation of the reliability constraints, the problem is formulated as a mixed-integer linear programming. An explanatory example is given to illustrate the advantage of the joint model comparing with the interval-based PM policy in terms of system's overall cost. A three-stage heuristic is proposed to solve this integrated model, which includes a Lagrangian-based heuristic for the CLSP. The numerical experiments are conducted to evaluate the performance of the developed heuristics and the computational results show that the heuristics can provide good feasible solutions for the corresponding models. The discussion of the results is finally given in detail.