A Detailed Case Study on Performance Assessment of Manufacturing

This case study provides a detailed performance assessment of a manufacturing plant, focusing on business and site information, opportunities and benefits, performance measurement, and key performance indicators (KPIs). The assessment covers various operational levels, including manufacturing added value, customer service, reliability, control flexibility, stocks, and people. It identifies potential improvements in areas such as plant output, first-pass efficiency, product consistency, and uptime. The study highlights the importance of routine measurement and monitoring to enhance manufacturing processes and achieve organizational goals. The performance index indicates the effectiveness of the organization's operations and the feasibility of achieving further improvements through targeted strategies based on KPI analysis, emphasizing the need for consistent assessment and adaptation to changing conditions.

Manufacturing Systems
Name of the Student
Name of the University
Author Note

Table of Contents
Part B...............................................................................................................................................3
Case Study: Performance Assessment of Manufacturing Plant..................................................3
1. Introduction..........................................................................................................................3
1.1. Business and site information...........................................................................................3
1.2. Opportunities and benefits................................................................................................4
1.3. Performance assessment...................................................................................................5
1.4. Performance index............................................................................................................6
1.5. Possible improvement options based on the key performance indicators (KPI’s)...........6
1.6 Conclusion.........................................................................................................................7
References........................................................................................................................................8

Part B
Case Study: Performance Assessment of Manufacturing Plant
1. Introduction
It is necessary that business performance of any organisation according to their
operations is assessed for manufacturing business. this enables the organisation to have a look at
whether the operations within the company is being able to meet the business requirements as
well as the needs of the clients as meeting both the requirements of the business and clients is
extremely essential (Helleno, Moraes and Simon 2017). This further makes way for the
assessment of the organisation to be effective for every operation it performs at different level.
Therefore the following report would be based on the focus on performance assessment of the
manufacturing plants and businesses based on their business site and information, opportunities
and benefits assessment, performance assessment, performance index as well as the
improvement that would be based on the key performance indicator or KPIs.
1.1. Business and site information
The manufacturing industry has a business plan that can easily look forward to the
upcoming 7 years and is severely updated once every year. The updating of the business plans
can change more frequently as per the requirements or the changing conditions. The company
has an open communication system established within all the employees connected via Intranet.
The salaries are open to everyone and the organisation has the best of it Global competencies
comprising of almost 40,000 employees worldwide and anybody can apply for any kind of job
advertised on the internet (Hirayama and Nagasaka 2017). The site manager and operators has no
intermediate managerial levels and it is the same for all the branches worldwide. Although there

are different job grades, there are only five levels between the operators and the team that is self
managed. The strategic blueprint and philosophy within the organisation has been in a Dow since
five years.
1.2. Opportunities and benefits
In this section the potential benefit of the organisation would be justified with some
question asked about the potential of improvement within the organisation as for the information
provided by the facilitators (Khaleel et al. 2017). The questionnaire and the information provided
by the facilitators have shed light on several factors. It says that the organisation can have
increased plant outputs as well as the capacity of first pass efficiency can also be improved
within the organisation. It also provide the information that product consistency can be improved
and plant up time can be provided as well. There is a chance that frequent grid rate of changes
can be made so that average time for product specification changes can be reduced. The product
delivery performance and cost and also be improved to see that the final product has reduced
stocks. There are even chances that the material and source good delivery, reliability and quality
can be improved by reducing the stocks. The manufacturing of the products would help the
customers to add value to the organisation as well as the total cost of maintenance and also be
reduced. The entire estimated value of the annual improvements assumes that the organisation
can sell additional production at the current market prices as well with the total estimated
potential benefit of about 4,848 GBP (Khan and Turowski 2016). In addition to that, working
closely with the customer has a potential that the organisation can reach its increase target of 1.5
% RAV by 363,636 GBP. The total profit is estimated to be 1.2 million GBP.

1.3. Performance assessment
The performance assessment for the organisation is based on various levels of operations
in the organisation and their routine measures. All the performance assessment depends upon the
measurement taken of the added value or services by the organisation in a routine manner.
It has been found that the manufacturing of the products had added value for every
manufacturing employee in the plant having a profit of almost 430,848 GBP (Mourtzis, Fotia and
Vlachou 2016). When it comes to customer service the delivery of performance percentage has
been increased by 98% and the other is to production plant percentage has been increased by
80%.
The customer complaints percentage of the orders delivered have also dropdown to a
0.4%. the reliability and consistency are assessed later to find that the production rate has
increased by 90%, the quality rate has increased by 95%, and the scheduled and time and
unscheduled I'm time percentage of capacity has been routinely measured to be 20% and 79%
respectively. At the same time the calculated OEE and the maintenance cost percentage for
replacement of asset value has been 10% (Feng et al. 2017). The control flexibility has been
assessed to find out that the process capability is regularly measured and it has remained just the
same as before but the change of time of routine tasks affecting the production including the
great changes has been almost 600 in number. The stocks have been adding value to the material
and so stocks by increasing the sales by 606,061 GBP (Hirz and Ernst 2017). On the other hand,
the change value of work in progress has become minimal so as the engineering spelling and
storing time. The value of finished goods stocks in total value of stocks had increased in a huge
number and so is the Stocked on decreased by 11 lbs. The absenteeism in people has reduced by
1.5 % and the safety. Environmental performance has been on its full potential as well as average

trainings given to per employee has been a total 10 in number. after the assessment of the entire
organisation and its operation including manufacturing, customer service, reliability, control,
flexibility, stocks and people, it can be said that the organisation has improved by 46% of its
previous assessments (Katayama and Lee 2018).
1.4. Performance index
The performance indicator depict how will the organisation and its operation are working
where as performance index would be regarded as the calculated factor in finding out the
feasibility of the entire system and how effectively it works to achieve the goals that the
organisation has previously set for having an improvement (Farias et al. 2015). Given all the data
of the performance assessment and the information of the organisation it can be said that the
business insight information is clearly depicted that the organisation has achieve the
improvement that it had decided to put forward. It is easier to understand that the business needs
effective and providing the performance analysis in accordance to the entire organisation. The
managerial bodies have been able to understand the benefits of the organisation and its
operations that we required to bring about the changes (Mourtzis et al. 2018). The performance
index also indicates that the performance within the organization been going on in an effective
way and it has already been seen that achieving further targets to have more improvements
would not be a distant idea.
1.5. Possible improvement options based on the key performance indicators (KPI’s)
The case studies presented in this matter regarding the manufacturing systems and the
organisation performing the manufacturing of the products from the raw materials, it can be
clearly seen that performance assessment is formed by the various average figures within the
entire organisation and its operation that has not been measured in a routine (Liu et al. 2015).

The most important amongst all of the processes within the organisation in suspecting the
possible improvement based on the key performance indicator or KPIs can be regarded as the
change of time of the routine processes that affects the progression of a task and the capability of
that process in bringing about the improvement. The delivery performance percentage is not
assessed in a regular manner and therefore the organisation should other to the production plant
percentage as well as the delivery performance percentage (Goto et al. 2016). Both of these
operations assessment should be performed in a much improved manner and should be measured
in a day to day basis to find out the overall improvement in the manufacturing organisation.
1.6 Conclusion
Therefore, in conclusion it can be said that the manufacturing organisation takes care of
every operational process that it goes through in the business insight information, opportunities
and benefits, performance index, process performance and assessment, and the possible
improvement options based on the key performance indicators or KPIs. Based on all the
information provided by the entire organisation regarding the above mentioned factors it was
seen that how this operation systems where dependent on each other and performing on the basis
of having a positive change on improvement within the organisation. Assessment and day to day
monitoring would improve and enhance the way of manufacturing process within the entire
organisation.

References
Farias, F., Johnsson, C., Ramminger, G. and Lima, L., 2015. Key Performance Indicators for
Monitoring and Evaluation of PID and APC Strategies at Manufacturing Operations
Management Level in a Natural Gas Processing Unit. In 12th International Symposium on
Process Systems Engineering and 25th European Symposium on Computer Aided Process
Engineering.
Feng, S.C., Kibira, D., Brundage, M.P. and Morris, K.C., 2017, June. PROCEDURE FOR
DEVELOPING KEY PERFORMANCE INDICATORS FOR SUSTAINABLE
MANUFACTURING. In ASME 2017 International Manufacturing Science and Engineering
Conference.
Goto, S., Trolio, E., Yoshie, O. and Tamaki, K.Y., 2016, July. Multi-party interactive
visioneering workshop for smart connected products in global manufacturing industry
considering PLM. In IFIP International Conference on Product Lifecycle Management (pp. 501-
511). Springer, Cham.
Helleno, A.L., de Moraes, A.J.I. and Simon, A.T., 2017. Integrating sustainability indicators and
Lean Manufacturing to assess manufacturing processes: Application case studies in Brazilian
industry. Journal of cleaner production, 153, pp.405-416.
Hirayama, K. and Nagasaka, Y., 2017. An Application of the Most Effective KPI in Business
Management—Development and Application of KPI Pool. Holistic Business Process
Management: Theory And Pratice, 14, p.37.

Hirz, M. and Ernst, M., 2017. Development and manufacturing process optimization of
mechatronics products by innovative key performance indicators. In MOTSP 2017-International
Conference Management of Technology–Step to Sustainable Production.
Katayama, H. and Lee, D.J., 2018. Extension of KPI measures for effective lean management-
Some evolutional directions for more leanised organisation.
Khaleel, H., Conzon, D., Kasinathan, P., Brizzi, P., Pastrone, C., Pramudianto, F., Eisenhauer,
M., Cultrona, P.A., Rusinà, F., Lukáč, G. and Paralic, M., 2017. Heterogeneous applications,
tools, and methodologies in the car manufacturing industry through an IoT approach. IEEE
Systems Journal, 11(3), pp.1412-1423.
Khan, A. and Turowski, K., 2016. A survey of current challenges in manufacturing industry and
preparation for industry 4.0. In Proceedings of the First International Scientific Conference
“Intelligent Information Technologies for Industry”(IITI’16) (pp. 15-26). Springer, Cham.
Liu, X., Yu, S., Li, Z. and Jiang, L., 2015, September. Developing a Performance Evaluation
System Based on Key Performance Indicators for Discrete Manufacturing Workshop.
In Conference on Engineering And Technology Management GCETM-2015 (p. 297).
Mourtzis, D., Fotia, S. and Vlachou, E., 2016. PSS design evaluation via KPIs and lean design
assistance supported by context sensitivity tools. Procedia CIRP, 56, pp.496-501.
Mourtzis, D., Fotia, S., Vlachou, E. and Koutoupes, A., 2018. A lean PSS design and evaluation
framework supported by KPI monitoring and context sensitivity tools. The International Journal
of Advanced Manufacturing Technology, 94(5-8), pp.1623-1637.