Systematic Literature Review of Statistical Process Control in the Service Industry

This systematic literature review explores the application and benefits of statistical process control in the service industry. It discusses the issues in the service sector, the concept of statistical process control, its modern application, and the utilization and implementation of SPC. The review also examines the use of SPC in food services and highlights its advantages in ensuring quality and safety. Overall, this review provides valuable insights into the use of SPC in the service industry.

Running head: SYSTEMATIC LITERATURE REVIEW OF STATISTICAL PROCESS
CONTROL IN THE SERVICE INDUSTRY
SYSTEMATIC LITERATURE REVIEW OF STATISTICAL PROCESS CONTROL IN
THE SERVICE INDUSTRY
Name of the Student
Name of the University
Author Note

1SYSTEMATIC LITERATURE REVIEW OF STATISTICAL PROCESS CONTROL IN
THE SERVICE INDUSTRY
Table of Contents
Literature Review.......................................................................................................................2
Introduction............................................................................................................................2
The issue in the service sector................................................................................................2
Statistical Process Control......................................................................................................3
The modern application of the process..................................................................................3
Utilisation and implementation of SPC..................................................................................5
SPC and food services:...........................................................................................................7
References..................................................................................................................................9

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Literature Review
Introduction
There are a number of researchers who have provided several frameworks for the
practitioners and the managers who want to introduce and implement the control charts in the
sectors apart from the manufacturing sectors. The consumers are very much aware of the
products and the services that they use and the recent consumer market faces an increasing
demand for the best quality of products and services. The customers want to get the
maximum satisfaction by paying the minimum amount and similarly the companies want to
achieve the maximum profit by incurring minimum costs. The concept of quantity and quality
is therefore an important matter of concern for all the organisations. A proper quality and
quantity management must be therefore there in the organisation. This management can be
done with the process of Total Quality Management, which can be done by using the
statistical processes (Aquilani et al. 2017).
The issue in the service sector
The poor quality of services creates a dissatisfaction among the customers and have
several severe consequences that even affects the health of the employees. The software
development industries are one of the major service industries. One minute fault in the
software will have a devastating effect on the individuals. A software failure in the radar
system of the patriot missile at the time of the Gulf War let the Iraqi Scud to enter into their
defense system of air and there after killing around 28 peoples by hitting the American
barracks of Saudi Arabia. In the year 1996, there was a failure in the launch of the maiden
flight related to Ariane 5 launcher (Hauschild et al. 2017). The reason this launch was a
failure was because of the problem in the software with the proper conversion of data.

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Statistical Process Control
The statistical process control is widely used in the manufacturing industries as well
as the service industries. Statistical process control is done by inspecting the service quality,
the deviation in the quality and thereafter by determining the necessary corrections that are to
be taken. The above mentioned incidents clearly states that this statistical process is very
important for the organisations in order to prevent themselves form any kind of serious
issues. These incidents clearly shows the needs and the requirement of monitoring the defects
in the complex software and other services and thereafter reducing the same. This can be
achievable by using certain measures like the rate of inspection, the rates of reviews, rate of
removal of defects, the defect density, defect injection distribution and the effectiveness of
inspection process.
Almost about 50-80 percent of the time is spent on the defect testing and repairing, by
the employees engaged in the software development procedures. If the defect stays for a
longer period of time, it will become harder to fix. The identification and the fixing of the
problems after the delivery is very much complex than the identification and the fixing of the
problems at the introductory phase (Lv et al. 2017).
The modern application of the process
There has been a shift from the defect correction to defect prevention strategy in
relation to the quality control process in the service industry. The traditional analysis and
testing of the software is no more given importance and rather the concept of the statistical
process and control system is applied for controlling the processes producing the software
products. The SPC is a very famous approach that helps in the identification, monitoring,
understanding and improvement in the overall service processes and the performances
throughout the time period. It has been used in the service sector for a long period of time,
with an increase at the time of the Second World War. The introduction and the application

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of the Six Sigma Program has intensified the concept of the SPC (Albliwi et al. 2014). The
process helps in a stabilised and consistent output that is controlled by the analysis of any
deviations and the corrective measures needed to be done on order to remove the deviations,
and it includes the evaluation of the capability of the process. There is a control chart through
which the visual signals are being provided and the SPC relies on such control charts when
any of the processes are out of control. The SPC chart approach is an important tool and its
approaches in the different non-standard applications results in several complications and
challenges.
The processes that are suitable for SPC are clearly defined, continuous, measurable
and critical enough to be justified. There are several factors by which the implementation of
the SPC is affected and they are numerous and complex in nature. These factors are called as
the Critical Success Factors (CSF) (Madanhire and Mbohwa 2016). The better the control on
these factors, the better will be the success of the implementation of the same. In case of the
service sectors the implementations are needed to be properly done else it would result to
very severe aftereffects. In case of software development services, it is very different process
from that of the normal processes. The software stabilisation and improvisation process is
very complex than the manufacturing process control systems. The service expected and the
service provided are not always the same as there will always be a little amount of deviation
in case of providing services. In cases of the manufacturing units, it is totally different, that is
the product provided must be matched with the product that is expected by the market. The
measurement tasks in the service sectors are difficult than that of the manufacturing sectors
and it involves a specific time period, the nature of the service, the number of the defects
detected in the service, the type and the time taken to eliminate those defects (Khorshidi,
Gunawan and Nikfalazar 2016). Most of the manufacturing tasks are repetitive in nature but
not all the services that are being provided are of repetitive nature. The service sector

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involves continuous development in the delivery of the service as well as the structure of the
service. One single service can be provided using numerous techniques and it also involves
innovation. The incomplete concepts and ideas on the service quality results to the
underutilisation of the SPC techniques in the services industry (Mirzaei, Niroomand and Zare
2016).
Utilisation and implementation of SPC
Statistical process control is one unique process of measuring the quality during the
process of manufacturing depending upon specific standard and controlling the process for
achieving quality. For the service industry represented as an application with the real data
into the commercial company. This has a unique measurement and process controlling
method ad this differs from the controlling and measuring the process for manufacturing
concerns. Hence, this process has been named as the non-manufacturing process (Godina
Matias and Azevedo 2016). Quality data into the form of process measurement are collected
during the in real time during the manufacture. While into the next step the data has been
plotted on a graph depending on the predetermined control limit. Data which fails with in the
control limits represents that eve thing has been operated as expected. If any variation with in
the control limits has been recognized this is because of the general cause as the natural
deviation is expected to be as a procedure step. However if data falls outside of the
controllable limits, it indicates towards the assignable cause is likely the source of the product
variation. Further this indicates that with in the process requires to be changed so that the
issue can be fixed before any defects occurs. This has been recognized that the service and
the manufacturing sectors are benefited by the use of SPC tools from the several situation. As
per the principles and the framework of the SPC developed for the service industry has aimed
towards the quality philosophy on all process. Further the practical application of demining
the philosophy for services has been investigated. The SPC framework has helped in activity

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monitoring in telecommunication industry which helps in monitoring customer profile
evaluation through a group of state specific equation (Sarkis et al., 2014). This has been
implemented through the four steps followed by
1. Process definition.
2. Process diagnosis.
3. Action and measurement.
4. Design for control chart.
The SPC has been widely used as a comparison to worth in the service environment
of the customers. It needs to be identified that the SPC makes use of control chart to measure
and specify when to adjust a process or when the process in out of statistical control. This
also has been recommended that the SPC should be developed for the generation of the
customer satisfaction rather than making it as a part of organizational strategic planning.
Hence in many organization this has been recognized the SPC initiative fails to performed
adequately because of because of lack of knowledge about the and its application within the
organization. However the successful application of the SPC method in the organization
requires a mixture of planning skill, engineering skill, management skill, statistical skill
communication skill (Hazen et al., 2014). For the successful and best implementation of this
method into the industry setting this process illustrates a conceptual frame work which takes
all the critical factors into the account (Madanhire and Mbohwa 2016). However, furthermore
problems into the implementation of the SPC in the organization has been recognized in the
lack of obligation and involvement of the top management, lack of providing training and
development of the SPC method to the organizational people, failure to interpreted the
control chart that are generated from SPC, Invalid and incapable measurement system at
workplace (Jin, Jang and Sun 2015). Finally the advantage of using SPC has been recognized

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as this generates a quality management criteria which provide added advantage over the
company’s service generation for the consumer (Azizi 2015).
SPC and food services:
The literature reveals how SPC will be applied and advantages of applying SPC
system in food services industry. The topic focuses on not only processing but packaging of
food products. The study also reflects the SPC control system uses in a fish processing
industry where the low control limit ignores the under filing process as well as the upper
control limit on over filing. The process includes improving food safety, increasing
correlation plan in validation, and increase in continuous opportunity for performance
development and provide quality information to the customers. Food safety are of great
importance. The companies must therefore ensure that proper certification is provided by the
companies measuring the food safety. For the monitoring of the critical control points under
the process HACCP and to access the process trends which may disrupt the limits. However
the food processing industry played an important role in quality control and safety
measurement. The case study have suggested that the food company have detected out of
control CCP and restrained from production stopping or reproducing. It has been however
observed that the obstacles that the companies mainly face ensures the data normality, which
is hardly found in the food industry. Apart from that the solid evidence found from several
case study have suggested that food industry have some advantages in having the SPC
implementation. But the same is been lagging behind the on case of the other manufacturing
agencies. Recently there has been an observation on taking 35 European industrial food
corporations reveal that only five companies have implemented SPC policy within their
organization. Apart from that the other findings suggests some interesting factor which
includes that the SPC technique is one of the least implemented quality controlling

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techniques as compared to the visual implementation. According to the analysts change
resistance is the main debatable factor of the food industry. Other than that the understanding
in statistical thinking results in the change in reluctance and callousness to consider the
statistical based barrier quantity tools that till now have bit ben studies empirically (Lim et
al., 2014). Apart from that that it is also been observed from the study of the literature review
that using of SPC in the food organization is considered to be helpful for measuring the
quantities and qualities of the product. However the same can be changed by using the
control chart. However it is also being mentioned that the SPC chart is helpful for food
manufacturing industry and it is considered to be helpful for the company also in a long term
basis (Dora et al., 2013). Apart from that the upper control line and the lower control line are
provided to be helpful for measuring the quantities and qualities of the product (Halim et al.,
2017). Hence it is going to be a good option is checking the quality and safety if the products.
Furthermore the literature have been formed by SPC managerial aspects, neglecting the
managerial research importance and elements of operations such as CSF’s (Shih et al., 2016).
Therefore the survey is proposed to fill the gaps in the research on the topic and also takes
care of the operational performance.

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References
Albliwi, S., Antony, J., Abdul Halim Lim, S. and van der Wiele, T., 2014. Critical failure
factors of Lean Six Sigma: a systematic literature review. International Journal of Quality &
Reliability Management, 31(9), pp.1012-1030.
Aquilani, B., Silvestri, C., Ruggieri, A. and Gatti, C., 2017. A systematic literature review on
total quality management critical success factors and the identification of new avenues of
research. The TQM Journal, 29(1), pp.184-213.
Azizi, A., 2015. Evaluation improvement of production productivity performance using
statistical process control, overall equipment efficiency, and autonomous
maintenance. Procedia Manufacturing, 2, pp.186-190.
Dora, M., Kumar, M., Van Goubergen, D., Molnar, A. and Gellynck, X., 2013. Food quality
management system: Reviewing assessment strategies and a feasibility study for European
food small and medium-sized enterprises. Food control, 31(2), pp.607-616.
Godina, R., Matias, J.C. and Azevedo, S.G., 2016. Quality Improvement With Statistical
Process Control in the Automotive Industry. International Journal of Industrial Engineering
and Management (IJIEM), 7, pp.1-8.
Halim Lim, S.A., Antony, J., Arshed, N. and Albliwi, S., 2017. A systematic review of
statistical process control implementation in the food manufacturing industry. Total Quality
Management & Business Excellence, 28(1-2), pp.176-189.
Hauschild, A., Markgraf, M., Montenbruck, O., Pfeuffer, H., Dawidowicz, E., Rmili, B. and
Conde Reis, A., 2017. Results of the GNSS receiver experiment OCAM-G on Ariane-5 flight
VA 219. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of
Aerospace Engineering, 231(6), pp.1100-1114.

10SYSTEMATIC LITERATURE REVIEW OF STATISTICAL PROCESS CONTROL IN
THE SERVICE INDUSTRY
Hazen, B.T., Boone, C.A., Ezell, J.D. and Jones-Farmer, L.A., 2014. Data quality for data
science, predictive analytics, and big data in supply chain management: An introduction to
the problem and suggestions for research and applications. International Journal of
Production Economics, 154, pp.72-80.
Jin, C., Jang, S. and Sun, X., 2015, April. Structural damage detection using extended
Kalman filter combined with statistical process control. In Sensors and Smart Structures
Technologies for Civil, Mechanical, and Aerospace Systems 2015 (Vol. 9435, p. 94352K).
International Society for Optics and Photonics.
Khorshidi, H.A., Gunawan, I. and Nikfalazar, S., 2016. Application of fuzzy risk analysis for
selecting critical processes in implementation of SPC with a case study. Group Decision and
Negotiation, 25(1), pp.203-220.
Lim, S.A.H., Antony, J. and Albliwi, S., 2014. Statistical Process Control (SPC) in the food
industry–A systematic review and future research agenda. Trends in food science &
technology, 37(2), pp.137-151.
Lv, F., Wang, H., Kong, D., Chen, X., Yue, Y. and Fang, P., 2016. Quality Management in
Pellet Feed Mill Based on Statistical Process Control (SPC). In 2016 ASABE Annual
International Meeting (p. 1). American Society of Agricultural and Biological Engineers.
Madanhire, I. and Mbohwa, C., 2016. Application of statistical process control (SPC) in
manufacturing industry in a developing country. Procedia Cirp, 40, pp.580-583.
Mirzaei, N., Niroomand, S. and Zare, R., 2016. Application of statistical process control in
service industry: A case study of the restaurant sector. Journal of Modelling in Management,
11(3), pp.763-782.

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THE SERVICE INDUSTRY
Sarkis, G., Giard, P., Vardy, A., Thibeault, C. and Gross, W.J., 2014. Fast polar decoders:
Algorithm and implementation. IEEE Journal on Selected Areas in Communications, 32(5),
pp.946-957.
Shih, C.W. and Wang, C.H., 2016. Integrating wireless sensor networks with statistical
quality control to develop a cold chain system in food industries. Computer Standards &
Interfaces, 45, pp.62-78.