Establishing and improving manufacturing performance measures

Robotics and Computer Integrated Manufacturing 18 (2002) 171–176

Establishing and improving manufacturing performance measures

M. Munir Ahmada,*, Nasreddin Dhafrb

aProcess Manufacturing and Design, School of Science and Technology, University of Teesside, Middlesbrough TS1 3BA, UKbOperation and Production, Jowfe Oil Technology, Libya

Abstract

This paper sets out the basis to establish key performance indicators (KPIs) in manufacturing companies. Their significance and

how they can be used to make improvements. KPIs has been chosen in order to deal with the possibility of improving the utilization

of a process manufacturing plant. The objective is to present a new methodology for KPIs. Also methodologies on manufacturing

performance measures taken from the literature are used for the solution of improving the utilization. They are discussed on the

basis of a manufacturing experience. In this paper, a presentation of these methodologies, a critical evaluation and short examples of

applying them are included. The main conclusion of this paper is that the KPIs can be used quantitatively in assessing the

manufacturing performance of a company. r 2002 Published by Elsevier Science Ltd.

Keywords: Performance measurement; Manufacturing improvement; Key performance indicators

1. Introduction

Key performance indicator (KPI), is a number orvalue which can be compared against an internal target,or an external target ‘‘benchmarking’’ to give anindication of performance. That value can relate todata collected or calculated from any process or activity.The selection of a range of performance measures

which are appropriate to a particular company ought tobe made in the light of the company’s strategicintentions which will have been formed to suit thecompetitive environment in which it operates and thenature of business. For example, if technical leadershipand product innovation are to be the key source of amanufacturing company’s competitive advantage, thenit should be measuring its performance in this arearelative to its competitors. But if a service companydecides to differentiate itself in the marketplace on thebasis of quality of service, then, amongst other things, itshould be monitoring and controlling the desired level ofquality.Whether the company is in the manufacturing or the

service sector, in choosing an appropriate range ofperformance measures it will be necessary however tobalance them, to make sure that one dimension or setof dimensions of performance is not stressed to the

detriment of others. The mix chosen will in almost everyinstance be different. While most companies will tend toorganise their accounting systems using commonaccounting principles, they will differ widely in thechoice, or potential choice, of performance indicators.There are short-term measures which have to becontinually calculated and reviewed. These measurescan represent [1]

* a financial performance indicator (business perfor-mance);

* a technical performance indicator (productivitymeasurement);

* an efficiency indicator (human contribution measure-ment).

It is very clear that by focusing only on results,more harm than good can be achieved. Metricsare absolutes and do not explain why things are sogood or bad and the decisions made based onabsolute numbers/ratios/percentages, could be verydetrimental to the businesses concerned in the longterm [1].Also when taking the manufacturing productivity as

an example of an internal KPI that measures theoperational efficiency of a manufacturing organization.Many organizations use efficiency metrics that onlymeasure a portion of the true productivity. Incompletemetrics may lead to inappropriate action.

*Corresponding author. Tel.: +44-1642-218-121; fax: +44-1642-

342-067.

0736-5845/02/$ - see front matter r 2002 Published by Elsevier Science Ltd.

PII: S 0 7 3 6 - 5 8 4 5 ( 0 2 ) 0 0 0 0 7 - 8

Performance areas must be operationalised, that is,made measurable, in the form of performance indicatorsin order for the company to be able to monitorperformance and goal realisation. The first internationalmanufacturing strategy survey (IMSS), carried out in 20countries around the globe, found that companies use avariety of indicators to measure their company andmarket performance [2].

2. KPIs for manufacturing performance

It was considered that the KPIs within the manufac-turing strategy are cost, quality, flexibility and delivery,as well as inventory [3]. A part of a project survey wascarried out to identify which performance indicatorscompanies use and which ones they characterise asimportant. The top five were: profitability, conformanceto specifications, customer satisfaction, return oninvestment and materials/overhead cost. When lookingat the performance areas to which the specific indicatorsare related and considering their relative importance itwas also possible to rank the importance of performanceareas (from top to bottom): efficiency, quality, compe-tence (technical), flexibility, innovativeness, speed andcapacity [2].

3. Measurement methodology

An improved methodology should be used to measureall aspects of manufacturing productivity. This enablesthe organisation to view productivity from the stand-point of the entire system. A suitable measurementmethodology enables senior management to focus scarceresources on elements that have the greatest impact onproductivity. Companies, who have this, have been ableto achieve additional production capacity, often withoutlarge capital expenditures for additional machinery ornew technology.Some manufacturing assessment methodologies were

available to us and were compared; a methodology wasintroduced in [4], an example of this methodology isshown in Fig. 1. In this methodology, we are unable todraw a quantitative performance measure, as themajority of the assessing elements on it are qualitative.The methodology introduced in [5], which is shown inFig. 2 has been adopted from EFQM, which is alsobased on qualitative assessment. Another methodologywas introduced in [6], an example of it is shown inFig. 3. In this methodology, we can assess the perfor-mance in a quantitative way, and there are a supportingformulas which can help when generating data from thepractice and assessing an accurate performance.

A6. Please tick the statement which best describes your customers’ perception of your products:

Your customer expectations are exceeded

Your customers are very satisfied

Your customers are satisfied

Your customers are sometimes satisfied

Your customers are indifferent

Our customers are sometimes dissatisfied

Your customers are dissatisfied

Your customers are very dissatisfied

Your customers are extremely dissatisfied

Fig. 1. An example of a questionnaire used to assess manufacturing [4].

PROCESS RESULTS

Score 1 2 3 4 5 6 7 8 9 10

Meeting customer

needs is clearly seen

byall as the purpose of

all activities.

Procedures and

operating standards are

owned by the

operators, managers

and suppliers.

The system ensures

that all stakeholder

needs are met by

existing and new

services. Customers

find iteasy to do

business with the

organisation. Feedback

leads to improvement

and innovation.

Few procedures exist

apart from financial

controls. Everyone

does their best and

firefighting is the

norm. changes are

made to fix problems

as and when

appropriate.

Procedures have been

written and imposed.

A bureaucratic system

exists with little

chance for

improvement.

Mistakes are seen as

‘bad’ but are rarely

used to make

improvements.

Critical processes are

owned and there is

support to monitor and

improve them.

Ownership is assigned

to management who

review corrective

action etc.

Fig. 2. An example of self-assessment matrix [5].

M.M. Ahmad, N. Dhafr / Robotics and Computer Integrated Manufacturing 18 (2002) 171–176172

The assessment and analysis of manufacturing per-formance introduced in [6], was covering the areas ofquality, delivery reliability, cost (price minus profitmargin) and delivery lead time. These performanceindicators were selected because they indicate importantaspects of manufacturing performance areas andare usually fairly easy to measure or estimate. Thecompany’s relative performance in each area for a plantor specific product (line) can be assessed throughcomparison of relevant performance indicators withinternal goals/standards, competitors and customerdemand as shown in Table 1. After comparisons aremade for all performance areas, an overview ofperformance gaps can be made. Since the importanceof each gap depends on the organisation’s environment,specific company policy and market situation, it requiresthe company to set priorities.The measured KPIs are normally split into 6 sections:(1) Safety & Environment (2) Flexibility (3) Innova-

tion (4) Performance (5) Quality (6) Dependability.Our focus in this paper will be on the KPI of the

dependability.

4. Dependability

This KPI consist of:

(1) customer complaints,

(2) on-time-in-full delivery to customers (OTIFc),(3) on-time-in-full delivery from suppliers (OTIFs),(4) overall equipment effectiveness (OEE).

4.1. Customer complaints

Measurement that identifies operational problemsthat might be avoided in future. It will be determinedby the number and nature of customers complaints inorder to identify operational improvement projects.Written, verbal and anecdotal information will berecorded. This data will be shared to avoid repeatproblems at other sites. The quality assurance depart-ment will be responsible to provide the informationrequired on a normal basis.The goal will be to achieve o1% complaints on

dispatches. KPIs measured are normally the number ofcustomer complaint received which are normally ex-pressed as an absolute number or as a percentage ofdispatches made. These complaints are not only relatedto dispatches but could arise from any business area.

4.2. On-time-in-full delivery to customers (OTIFc)

The purpose of this KPI is to measure the deliveryof the product on time and in full with no defects inthe product, packaging, transport arrangement or

Table 1

A selected results from year 2000 compared to the world-class performances and the process

No. Activity The manufacturing plant World class (benchmarking) Process

1 Output 4500 N/A 30,000

2 Uptime 200 days N/A 300

3 Product delivery performance (OTIF) 91% >99.9% 100

4 Adherence to production plan 80% >99% 100

5 Customer complaints 1% o0.01% 0

6 Product rate 49% >95% 100

7 Quality rate 94% >95% 100

8 Availability 83% >95% 100

9 OEE 38% >85% 100

10 Absenteeism 6% 1.8% 0

11 Average training days/employee 8 13 N/A

1. Do you routinely measure the % of On-Time-In-Full delivery (OTIF) delivery performance?

Yes No This year measure ............ Previous year measure .........

2. Do you routinely measure the customer complaints - % of orders delivered?


3. Do you routinely measure the % Product Rate?


4. Do you routinely measure the Overall Equipment Effectiveness OEE?


Fig. 3. An example from the KPI assessment [6].

M.M. Ahmad, N. Dhafr / Robotics and Computer Integrated Manufacturing 18 (2002) 171–176 173

supporting documentation. It will measure the abilityto adhere to the first agreed demand date for eachorder, and whether there were any problems withthe materials shipped. Supporting such a measureneeds a rigorous recording system either by the plantitself, or by the distribution company if this aspectis out-sourced [6]. The goal in this KPI will be to achievea value >99%.

4.3. On-time-in-full delivery from suppliers (OTIFs)

This KPI will measure the receipt of raw materialsand other supplies on time and in full with no defects inthe product, packaging, transport arrangement orsupporting documentation. Suppliers can dramaticallyaffect our dependability. It will measure the ability ofthe suppliers to adhere to the first agreed demand datefor each order, and whether there were any problemswith the materials received.The goal in this KPI will be to achieve a value >99%.

4.4. Overall equipment effectiveness (OEE)

This measure is designed to determine just howreliable our assets are and their capability to deliverthe outstanding performance expected from a worldclass operation.

OEE ¼ Product rate�Quality rate�Availability:

OEE works on the principle that the best manufacturingperformance is when a site operates to full capacityalways produces perfect product and never breaksdown. capacity usage, quality performance and break-down data will therefore be combined to determine theOEE. The manufacturing manager at the site will beresponsible to provide the information required on atimely basis.It was suggested [6] that an overall equipment

effectiveness of 85% for a batch type plant and 95%for a continuous plant. Since the benchmarking againstbest practices and established KPI is the basics forcontinuous improvement of an enterprise [7]. For batchplant this can be achieved by

Quality RateX95%; Product RateX95%

AvailabilityX95%

and for continuous plant

Quality Rate > 99%; Product RateX95%

AvailabilityX99%:

Also it is not uncommon for an existing process plant tobe operating with an OEE of o50%. The question ishow much higher OEE could be achieved, how could theprocess technology influence that value and what will bethe long-term target?

It is suggested that an OEE of 99% on the criticalequipment will be the future target. This can be achievedby

Quality Rate > 99:9%; Product Rate > 99:5%;

Reliability > 99:5%:

To achieve these the following practices should beimplemented.Six sigma performances, fully automatic start-up,

shutdown and fail-safe, intelligent measurement, totalaccurate dynamic models, multivariate statisticalprocess control, design for success not failure, andpredictive maintenance.

4.5. Quality rate

This is the amount of product that is right first timewith out adjustment, recycles and so on. To achieve thesix-sigma performance described previously, it is neces-sary to achieve a very high right-first-time rate.

Quality rate ¼Good production

Good productionþ Failed QC:

4.6. Product rate

The product rate is defined as the average rate that theplant operates divided by the best that has ever beenachieved.For losses measured in time

ð8760� time lost due to s=dÞ �MPR� tonnage lost due to being belowMPR

ð8760� time lost due to s=dÞ �MPR:

For losses measured in tonnes

ð8760�MPRÞ � P lost due to s=d� P lost due to being belowMPR

ð8760�MPRÞ � P lost due to s=d:

And in some cases, the actual losses due to being belowthe MPR are not accurately recorded. In this case, thecalculation of product rate is

ðGood productionþ potential make in periods of no demandþQCÞð8760�MPRÞ � P lost to s=d

:

4.7. Availability

The availability is defined as the number of hours theplant operates divided by the number of hours in a year.

8760� ðnumber of hours of total shutdownÞ8760

:

5. Examining the methodology against a manufacturing

case

The chosen methodology was applied to a specialitychemicals plant. Results were compared to the world


class performances and the designed process output asshown in tables. Another results for year 2001 are shownin Table 2.

5.1. Data analysis

We can see from Table 1 that there are gaps betweenthe manufacturing plant measures and the world classmeasures. These gaps have been identified as areas forimprovement. Table 3 highlights these gaps.The main factors which contribute to low manufac-

turing performance measures are shown in Figs. 4 and 5.they show that only 60% of time was spent on actualproduction, hence low OEE of 38% and 45%. Thefuture work will cover different production periods,products and plants (Figs. 6 and 7).

6. An improved measurement methodology

The assessment and analysis of manufacturing per-formance introduced in this paper is covering the areasof quality, delivery reliability, cost (price minus profitmargin) and delivery lead time. These performanceindicators were selected because they indicate importantaspects of manufacturing performance areas and areusually fairly easy to measure or estimate. In our case(the selected plant), measuring the performance of thewhole plant as one production line will not provide areal results, that is because of production aspect foundin this kind of plants, that is the company pursues thestrategy of make-to-order and the plant contains fiveseparate production vessels, normally these vessels noton operation all of them at the same time because of themarket demand, in sometimes only one or two or threevessels are in operation while the others staying idlewaiting for a production program. When there is aproduction, the only part of the plant runs all the time isthe utility which is shared between the productionvessels. As a result, applying the selected measurement

Table 2

A selected results from year 2001 compared to the world-class performances and the process

No. Activity The manufacturing plant World class (benchmarking) Process

1 Output 6947 N/A 30,000

2 Uptime 224 days N/A 300

3 Product delivery performance (OTIF) 69% >999% 100

4 Adherence to production plan 85% >99% 100

5 Customer complaints 3% o0.01% 0

6 Product rate 55% >95% 100

7 Quality rate 90% >95% 100

8 Availability 91% >95% 100

9 OEE 45% >85% 100

10 Absenteeism 4% 1.8% 0

11 Average training days/employee 7 13 N/A

Table 3

No. KPI Gaps

2000 2001

1 Product delivery performance 10% 50%

Adherence to production plan, 20% 14%

Customer complaints 5% 3%

Product rate 46% 40%

Availability 19% 4%

Quality rate 1% 5%

OEE 46% 40%

Absenteeism 4.2% 3.2%

Average training days 5 days 6 days

Fig. 4. Production period from 1/1/2000–31/12/2000.

Fig. 5. Production period from 1/1/2001–31/12/2001. ( ) Actual

production; ( ) High stock; ( ) Maintenance; ( ) Other reasons.

M.M. Ahmad, N. Dhafr / Robotics and Computer Integrated Manufacturing 18 (2002) 171–176 175

methodology to measure the performance of this plantwill not give right results about the real situation in theplant, since the results will be based on the runningvessels as this methodology will take into account thatthe plant is running regardless of the idle vessels, highresults on some performance indicators may be scoredwith the fact that more than half of the plant is idle, orlow results may score because of the low output of theplant. As a result of this aspect, it was decided tomeasure the performance for each vessel individually,and this gave to us many advantages since it is easiest tofind the places need improvements, as it gave us theability to monitor the strengths and the weaknesses ofthe production of each individual vessel and the relatedperformance.

After comparisons are made for all performanceareas, an overview of performance gaps can be made.Since the importance of each gap depends on theorganisation’s environment, specific company policyand market situation, it requires the company to setpriorities.An example of the suggested measurement procedure

is shown in Table 4.

7. Conclusions

There are many ways to raise the OEE. Some of theactions could be the training of operators, reviewing thebottleneck machines involving technical improvements,fine tuning of production schedules, redesigning ofproducts and improving the operating instructions.Some of these improvements may require substantial

investments. With good OEE measurement it is possibleto pick up the project with quickest returns. AccurateOEE measurement makes it possible to follow up theoutcomes of the development and investments.

References

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[2] Jose #AFBG, Harry B, Frank CM. Baudet University of Twente,

Enschede, The Netherlands Kostas Seferis TASIS, Athens, Greece,

CI and performance: a cute approach. Int J Oper Prod Manage

1999;19(11):1120–37.

[3] Corbett ML. Benchmarking manufacturing performance in Aus-

tralia and New Zealand. Benchmarking Qual Manage Technol

1998;5(4):271–82.

[4] Vic G, Maria G. A survey to assess the use of a framework for

manufacturing excellence. Integrated Manuf Systems 2001;12(1).

[5] Peter W. Management action notes. dti publications.

[6] Ahmad M, Benson R, Benchmarking in the process industries. Inst

Chem Engrs 1999.

[7] http://www.chemicals-technology.com/contractors/business/ids/.

Table 4

Comparison of the results of five production vessels

Annual output, tonnes (plant capacity) (drums) 30,000

Vessel V1 V2 V3 V4 V5

Planned throughput (forecast) 931 940 1304 1951 1747

Actual throughput 933 944 1326 1986 1758

Sales value 138,206 #### 299,192 478,124 361,931

Number of deliveries 17 14 18 12 12

Number of OTIF deliveries 12 11 14 7 7

% OTIF 70 78.57 77 58.33 58.33

% Customer complaints 1.9 5.26 2.2 3.85 3.41

Availability 0.95 0.9 0.93 0.9 0.89

Product rate 0.77 0.6 0.63 0.55 0.52

Quality rate 0.88 0.92 0.92 0.91 0.86

OEE 0.64 0.49 0.53 0.45 0.39

0.4

0.5

0.6

0.7

0.8

0.9

1

V1 V2 V3 V4 V5

Availability

Product rate

Quality rate

Fig. 6. The three components of OEE for the five production vessels.

OEE

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

V1 V2 V3 V4 V5

OEE

Fig. 7. The overall equipment effectiveness for the five production

vessels.


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Establishing and improving manufacturing performance measures