How Efficient is Your Packaging Machine and Packaging Line?

How Efficient are my Packaging Machines and Packaging Line?

The production department has sent you a report about their results and observations of each of the packaging machines at your facility and within the papers there is a tablet that tells how long each packaging machine along the line work and how many are lost in time and their causes.

And turning through the pages there is also data about the number of items produced and rejected numbers.

Report of Production

Modern management theory has a wide range of tools and methodologies to measure the packaging equipment throughput and the complete packaging line’s efficiency and efficacy so that the leadership and executives acquire an overall and holistic insight into their production and productivity to achieve constant improvement with their processes and packaging automation.

As the saying goes: 

And what is the point after measuring your production? The answers are:

• Analyze and reduce downtime, speed, and quality losses
• Maximize output from limited capacity

In this article, we are going introduce the concept of Overall Equipment Effectiveness (OEE), and another advanced quantitative tool of Total Equipment Effectiveness Performance (TEEP), which will help you with the measurement of how effective your packaging line and packaging equipment are.

What is Overall Equipment Effectiveness (OEE)?

Overall Equipment Effectiveness (OEE) is an associated metric that originated from a strategy called Total Productive Maintenance (TPM) to reduce and eliminate various production losses, which are called the “six big losses”, namely due to equipment failure, setup, adjustment, speed losses due to stoppages and defect losses for reasons of processes defects and reduced yield (Yick-Hin Hung, 2022) [2].

The TPM strategy has listed the below losses and then developed OEE as a metric to measure the in-use equipment’s effectiveness regarding its availability, performance, and quality. 

“Six Big Losses” Defined by TPM

In essence, OEE is a framework and quantitative tool for managers to spot the hidden issues that are dragging down their production efficiency and causing losses and shows the percentage of time that is actually productive. [3]

As follows is the formula to calculate Overall Equipment Effectiveness (OEE):

$$ \text {OEE} = \text {OEE}_\text{Availability} \times \text {OEE}_\text{Performance} \times \text {OEE}_\text{Quality} $$

Overall Equipment Effectiveness (OEE)
Credit: ELITER Packaging Machinery

What is Total Equipment Effectiveness Performance (TEEP)?

Total Equipment Effectiveness Performance (TEEP) is no more different than OEE but it applies a further component of Utilization Rate, that makes the calculation be

$$ \text{TEEP} = \text{OEE} \times \text{Utilization} $$

where

$$ \text{Utilization} = \frac {\text{Production Time}}{\text{All Time}} $$

TEEP takes into consideration the losses in the capacity that stem from the production being occupied as well as the unscheduled capacity.

How to Calculate Overall Equipment Effectiveness (OEE)?

The concept of OEE is quite simple. In the case of a packaging line or a single set of packaging equipment, it is a metric used to figure out how many hours during a workday has the equipment been actually productive and for how many hours it is not. It is also required to take into consideration those unproductive hours stem from scheduled, prevented, and planned works and procedures.

We have mentioned above the formula for calculating Overall Equipment Effectiveness (OEE) which is as below:

$$ \text {OEE} = \text {OEE}_\text{Availability} \times \text {OEE}_\text{Performance} \times \text {OEE}_\text{Quality} $$

And as the basic idea goes that OEE is about the valid percentage of production time that is truly productive, the very first step is to understand the Production Time

What is Production Time?

Confirming the production time is the fundamental step to start with the calculation of OEE.

Production time refers to the availability of packaging equipment during a specific period of time, with its planned downtime and unscheduled production.

Let total working hours be 8 hours, the calculation of production time would be:

$$ \text{Production Time} = \text{Total Working Hours}-\begin{pmatrix}
\text{Start-up, checking, test} \\
\text{Size changeover} \\
\text{Unscheduled production time} \\
\text{Any expected downtime} \\
\end{pmatrix} $$

To illustrate, a food processing and manufacturing facility would run from 09:00 am to noon, then 01:00 pm to 06:00 pm after a break, in total 8 hours a day for production. The production department schedules each day 15 minutes for start-up, checking, and test, and 15 minutes for a size changeover, which are excluded from the 8 working hours, then the production time would be 7 hours 30 minutes. 

With this concept explained clearly, we are now able to move forward with the calculation of OEE.

What is Availability in OEE?

The availability refers to the portion and ratio of production time during which the packaging machine is in operation – the so-called “Operation Time”.

The availability is a further component that excludes from the production time (which already has excluded the planned downtime) that unexpected downtime such as breakdowns, minor stoppages caused by jamming, reset, etc. In essence, it is a metric that assesses the losses in time. 

To calculate the Availability in OEE:

$$ \text{OEE}_\text{Availability} = \frac {\text{Operation Time}}{\text{Production Time}} = \alpha $$

Supposing a food processing and manufacturing facility of cereal in bags is running an automatic cartoning machine among its packaging line. The factory plans a production time of 8 hours each day. The mentioned time minus planned downtime would be the operation time.

Specifically according to the case:

$$ \text{OEE}_\text{Availability} = \frac {\text{Operation Time}}{\text{Production Time}} = \frac{\text{7 hours 20 minutes}}{\text{8 hours}} = \text{91.667%} $$

What is Performance in OEE?

Performance is a metric that evaluates the ratio of how much and the ratio of the machine’s maximum capacity has been taken avail of during the production time. 

The performance metric takes into account the losses in speed.

To illustrate, a cartoner machine is designed to run bags of cereal and pack them into cartons at a speed of 120 cartons per minute which means each cycle time last for 0.5 seconds. The result from this calculation is the Standard or Designed Cycle Time. Within a given period of operation time, for example. of 7 hours, the cartoner machine has produced 48,000 cartons filled with cereal bags, regardless of whether there are failures or rejected units or not and how many of them.

Then we will be able to proceed with the calculation of Performance in OEE:

$$ \text{OEE}_\text{Performance} = \frac {\text{Processed Amount} \times \text{Design Cycle Time}}{\text{Operation Time}} = \beta $$

In the previous case, we can get a result as:

$$ \text{OEE}_\text{Performance} = \frac {\text{48,000} \times \text{0.5}}{\text{7 hours 20 minutes}} = \text{90.909%} $$

But, what if the factory has simultaneous multiple sets of the same kind of packaging machines that are not connected as a line but working separately for the same product?

The case would more complex now that it is not necessarily that each of the cartoners here is set at the same speed as the rest. We will have 2 methods to proceed with the calculation of OEE Performance.

$$  \text{OEE}_\text{Performance} = \frac{\sum _{i=0}^n \frac{\text{Standard Cycle Time}}{\text{Cycle Time of Each Cartoner}_\text{i}}}{\text{n}}             \qquad (1)
$$

or alternatively,

$$  \text{OEE}_\text{Performance} = 1- \frac{\text{takt}}{ \sum _{i=0}^n  \text{Cycle Time of Each Each Cartoner}_\text{i} / n }                 \qquad (2) $$

Supposing that we have 6 sets of cartoning machines at the facility while each one of them is set at a different cycle time, the production time is 8 hours, and we have 210,000 units of packaging done.

at final we can proceed to the result of the Performance of OEE for such a case:
$$ \text{OEE}_\text{Performance} = 1 – \frac{\text{takt}} {\text{Cycle Time}_\text{Average}} = 1 – \frac{0.13}{0.95}= \text{86.32%} $$

What is Quality in OEE?

Quality is a metric that assesses the ratio and how much of the Proceesed Amount is good in quality. Or say, quality takes into account the quality loss.

The calculation is simply to exclude the amount that does not meet the quality standard, failed, and is rejected from production.

$$ \text{OEE}_\text{Quality} = \frac {\text{Processed Amount} – \text{Defect Amount}}{\text{Processed Amount}} = \gamma $$

Supposing among the 48,000 net units of filled cartons of cereal bags there are 850 units that are broken in packaging, then:

$$ \text{OEE}_\text{Quality} = \frac {48,000 – 850} {48,000} = \text{98.229%} $$

Get the Final Result of the OEE

Now that we have assessed the effectiveness of your packaging equipment, in terms of and among the Six Big Losses specified it TPM, the following losses.

• Losses in time
• Losses in speed
• Losses in quality

We are now able to proceed with the final calculation of your packaging equipment’s OEE:

$$ \text {OEE} = \alpha \times \beta \times \gamma = \text{91.667%} \times \text{90.909%} \times \text{98.229%} = \text{84.835%} $$

A Mathematical and Visualized Approach to the Calculation of OEE

Above OEE’s calculation involves the design cycle time which is the ideal and the shortest and minimum cycle supposed to produce each unit of product – or say, it is the most productive cycle time theoretically. Nevertheless, in an actual situation, the cycle time would not always comply with the most ideal cycle supposed now that the cycle time depends on a lot of factors such as defect losses, speed losses, and downtime (Nakajima, 1988, 5)

For example, a jamming in the packaging machine or the operator’s slacking-off especially with a manual-loading packaging machine are the primary factors that will drag the actual cycle time below the design cycle time.

To solve this problem, it is suggested to look to TEEP which takes into consideration of the time that is truly productive.[6]

$$ \text{TEEP} = \text{OEE} \times \text{Utilization} $$

Building Functions to OEE from TEEP Perspective

Set up a production function as follows:

$$ P: \mathfrak R_+^n \rightarrow \mathfrak R_+   , \text{produce output  } q \in \mathfrak R_+ \text{ where P(0) = 0}  \qquad (3)$$

Define the variable inputs by:

$$ \text{Vector x}=(x_1,x_2,x_3, … , x_n) \in \mathfrak R_+^n   \qquad (4)$$

The input requirement set should be:

$$ V(q) = {x\in \mathfrak R_+^n : (x,q) \in Q} \text{  where Q is the production possibility set}  \qquad (5)$$

Supposing period of time which is the total production time,

$$ t=1, 2, …, T   \qquad (6)$$

Define the capital input by:

$$ \text {Vector K} = (K_\text{n+1}, K_\text{n+2}, … , K_\text{n+m})   \qquad (7) $$

Define the time required to produce q, which is the result of the production function (3),

$$ \theta \in \mathfrak R_+  \qquad (8) $$

We are now able to build the function as follows according to the production function (3),

$$ q^t = P (x^t, K^t, \theta), K^t \le K, t=1,2,…,T, \qquad(9) $$

where P is defined by the isoquant that serves as a boundary to the input requirement set (5)

$$ I(q) = \begin{Bmatrix} x:x\in V(q) \text{ and } \lambda x \notin V(q) \text{ if } 0\le \lambda \lt 1 \end{Bmatrix} \qquad (10) $$

To explain the final function (9), suppose that a food processing and manufacturing company employs

$$
\begin{array}{ll}
x^t \text{as the variable inputs} \\
K^t \text{as the capital input, which is the size of the plan and can not exceed K no matter how many inputs given} \\
\text{then in a period of t with a required production time} \theta \\
\text{the company will produce } q^t \text{as the output} \\
\end{array}
$$

Define h(K), as the maximum capacity of the facility and cannot be exceeded, we will have:

$$ h(K)=  \underset{x^t}{max}P(x^t,K)  \qquad(11)$$

which is the same as TEEP when utilization is 100%, or say.

In ideal circumstances when OEE is 100% where there are not any losses at all, we will get

$$q_m = \frac {h(K)}{c} $$

where c is the ideal and standard, design cycle time. However, the c is impossible to reach considering the fact that “the cycle time depends on a lot of factors such as defect losses, speed losses, and downtime “.

Visualization Calculation to OEE

Based on the above functions we are now proceeding to build a coordinate system (supposing 2 inputs) as follows where

• VV’ is the isoquant function (10)
• WW’ as the slope of VV’ whose intersect D’ is the ratio of change of the two inputs
• E is a point the goes beyond the boundary VV’ now that a factory often has to take more time to produce a unit of packaging considering idles and downtimes, so that OE is the production time in OEE Availability (8 hours, for example, from 0900 am to 1200 am, 0100 pm to 0600 pm)
• C is the intersection of WW’ and OE, due to which OC is the design cycle time
• and OD as the actual cycle time (Operation Time in OEE Availability) due to speed losses so it is longer than OC

We are now able to calculate the OEE with the support of above visualization where;

Availability is:

$$ \text{OEE}_{Availability} = \alpha = \frac {OD} {OE} \qquad(12) $$

Performance is:

$$ \text{OEE}_{Performance} = \beta= \frac {OC} {OD} \qquad(13) $$

while the output of each packaging is either qualified to pass or unqualified to be rejected. Then Quality is:

$$
q(y) = \gamma =
\begin{cases}
\text{1}, & \text{qualified} \\[2ex]
\text{0}, & \text{not qualified, rejected}
\end{cases}
\qquad(14) $$

We are now able to proceed with the calculation of OEE which is:

$$  \text{OEE} = \alpha \times \beta \times \gamma =  \frac {OD} {OE}  \times \beta= \frac {OC} {OD}  \times \gamma = \frac {OC} {OE} \times \gamma \qquad (15)  $$

Why is OEE Important for Packaging Automation?

Whether it is for co-packer (Contract Packaging Companies) or for final users like a food production and processing company, setting a benchmark or yardstick to assess their Key Performance Index (KPI) is a critical step that can help with their decision-making and achieve improvement. OEE is no different than other indexes and tools like Six Sigma to drive improvements within the production.

Taking advantage of OEE is more affordable than a Machine

In the packaging industry, the decision to implement a packaging machine is carefully taken considering the significant set-up cost and the nature that this is such an irrevocable investment that once the machine has been installed it is impossible to replace it, or at least, would be of the incredible sunk cost that cannot be recovered. After the successful commissioning and installation of the packaging equipment, it is all about extracting more and more productivity from the equipment which is later converted into an asset.

Analyzing the shortcoming of the production with OEE can help to activate the potential and buried productivity that is hidden behind the production waste (Losses in Availability and quality) and cycle waste (Losses in Performance), to trim time off the process and unnecessary downtime avoiding compromising capacity,  and go beyond the current production ceiling.

OEE helps to identify the problems and facilitate the preventive maintenance

The calculation of OEE starts with the data-collection, logging, and records of packaging equipment and provides critical insights into the equipment’s productivity and would list those losses defined by the “TPM Six Big Losses”. The compiled information can facilitate the plant and production manager’s assessment and spot the potential downside and shortcoming that is deteriorating productivity.

Respectively, the leadership will plan and implement preventive and predictive maintenance strategies against those recorded losses and thus ameliorate the production to an optimal efficiency.

For instance, if OEE data reveals that there is a consistent reduction in overall production speed (performance loss), it may indicate the need for changing a particular component part, lubrication requirements, recalibration of sensors, or poor sequencing to align the machine/s with the intended output. These can be tackled proactively during planned downtime to avoid more complex issues later in the production cycle and ultimately achieve higher levels of equipment performance, quality products, and cost reductions.

Maximize salable packaging units to get better ROI

The purpose of implementing OEE is to take maximum advantage of the available capacity and make the output stable by minimizing downtime and approaching design cycle time.  In the packaging automation industry and for the benefit of the packaging equipment user, while each unit of packaging and product produced stands for extra revenues, the downtime and breakdown correspondingly deteriorate their revenues and thus will drag their ROI.

The following is how can implement OEE achieve a better ROI:

• Increased Production Yield: Higher OEE indicates that production downtime is significantly reduced, which means more products are produced within the same time frame. This translates to an increase in the production yield of salable packaging units, which in turn increases revenue and profitability.
• Reduced Material Waste: When a packaging machine operates at a lower OEE, the possibility of material waste increases because of the equipment’s operational inefficiencies. Improving OEE through proactive maintenance and effective performance can considerably decrease the wastage of materials, which helps to cut down costs and generate better profits.
• Enhanced Product Quality: An optimized packaging machine running at a higher OEE produces a much higher quality of packed materials. The intricacies involved in achieving this state include regular preventive maintenance at optimal frequencies, upgrades of crucial parts, and timely adjustments, among others. Packaging machines that operate effectively with well-maintained parts ensure that the output products are of top-notch quality; therefore, minimize downtime and save thousands of dollars in repair and scrap.
• Improved Responsiveness and Flexibility: Improving OEE leads to increased responsiveness and flexibility of the packing machine when it comes to adapting to changes. Packaging needs often change, depending on factors such as demand fluctuations or regulatory requirements. A responsive and flexible machine allows quick adaption, reducing the delays in retooling and changing over product runs. This ensures that the operation style is fast-moving and efficient.

Request an OEE Calculator by ELITER Packaging Machinery

Are you with a headache with the calculation of OEE for your packaging automation and production?

We have elaborated an OEE calculator to facilitate your work and to help you track your productivity.

To request the calculator, send your inquiry to: info@eliter-packaging.com

Looking for Advanced Statistical Analysis Tools for your Packaging Process Management?

If you had had profound knowledge around mathematics and statistics, it would be a good ideat to assess your packaging automation process with some advanced tools from Six Sigma.

To find out more information, please click on the following picture to check “How to Use Process Capability Index for Packaging Equipment”

Advanced Statistical Analysis Tools for Packaging Process Capability
Credit: ELITER Packaging Machinery

Bibliography

• [1] How Efficient is Your Packaging Equipment? Labeling and Coding News, Promach, December 4th, 2014, https://www.labelingnews.com/2014/12/how-efficient-is-your-packaging-equipment-oee/
• [2] Yick-Hin Hung, Leon Y.O. Li, T.C.E. Cheng, Uncovering hidden capacity in overall equipment effectiveness management, International Journal of Production Economics, Volume 248, 2022, 108494, ISSN 0925-5273
• [3] isixSigma, Using OEE Metrics for All Process Steps, April 13, 2015, Michael Carver https://www.isixsigma.com/capability-indices-process-capability/using-oee-metrics-for-all-process-steps/
• [4] OEE in packaging: deceptively simple, Jun 28, 2013, Health Packaging, https://www.healthcarepackaging.com/machinery-materials/package-design/article/13287332/oee-in-packaging-deceptively-simple
• [5] Nakajima, Seiichi. “Introduction to TPM: total productive maintenance.(Translation).” Productivity Press, Inc., 1988, (1988): 129.
• [6] Calculate TEEP, https://www.oee.com/teep/