Doubling the capacity of a pharmaceutical packaging line while reducing the cost. Is that possible?

Quickly identifying the losses and convert into money

About the Company

a German family owned specialized pharmaceutical company, founded in the 80’s, with state of the art production facilities and a wide range of packaging equipment, performs specialized contract manufacturing and co-packing.

It seeks higher capacities and at the same time lower costs.

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The Request

In Co Packing and Contract Manufacturing the cost pressure is high. At the same time, more and more OEM manufacturers seek capacity outside of their own company.

The manufacturer turned to us, requesting to analyze the productivity, capacity and cost-saving opportunities. They provided existing OEE data in an Excel sheet.

 

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Our Approach

  • Our approach is based on 25 years of experience and implementation of OEE in more than 5000 different machines. We have proven over and over that severe increases in capacity and strong reduction in cost are possible.
  • The customer is fully focused on cleaning and setup and assumes there is not much potential left to improve, besides modifications to the equipment, requiring severe capital investment. We will visualize and show ALL the losses.
  • A manual OEE registration was present; we will use this in order to provide a rapid analysis.

Step 1:

Together with the customer, we selected a machine and a time slot that is considered to be representative for the situation in the facility.

We validate the used OEE definitions within the provided data. We also validate the correctness of the provided data.

We were able to adopt the definitions to the OEE Industry Standard and correct some minor flaws.

Step 2:

We entered several weeks of data into our OEE Coach software. Since OEE Coach validates all data with a series of intelligent validation mechanisms, we were able to detect several commonly made mistakes.

Step 3:

We did a first analysis on the data: See a few highlights in the OEE Analysis Section.

Step 4:

After the first OEE data analysis, we converted the information into financial values. See Financial Analysis Section.

Step 5:

Make a step-by-step master-plan for the transition: a plan that is collecting revenues almost instantaneously!

 

How to identify and eliminate undesired phenomena is our specialty.

 

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Capability Analysis

TEEP- OEE and OOE (Overall Operations Effectiveness) Availability

The first analysis is: How  are the assets being used? We start with 24/7 at 100% speed and 100% quality as the reference:

Pie chart TEEP time analysis

It is immediately clear: About half of the time the expensive equipment is not scheduled to run and from the scheduled time, 25% is unscheduled again and more, as can be seen below:

OOE pie

Conclusion 1: It is possible to run the current production (from 2 shifts) in 1 shift

If we let OEE Coach draw a full loss cascade we see the following full potential:

Loss cascade diagram

This means:

  • 16x24h data: Theoretically 1,7 Mio Blister
  • Theoretical in all shifts: 888K
  • Theoretical in used shifts: 668K
    • Actual output: 232K
    • 13,5% Effectivity (=TEEP)
    • 26,3% Full  (=OOE)
    • 34,9% Actual shift Effectivity (=OEE)
Conclusion 2: 
This equipment could bring 5 times the current output 
(5 x 13,5% = 67,5%) and would still allow enough time for maintenance, setup’s etc.
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Availability Analysis

How is the scheduled time being used?

In the next analysis we reveal: How does the machine loses scheduled time? What makes it stop?

OEE Pareto chart waiting time
Again, visually it shows immediately: Unscheduling the machine during a shift is the biggest reason where capacity gets lost. We knew this already. But also regular- and extended breaks, technical breakdowns and setups consume a large portion of time: All causes that can be relatively simple eliminated!

How about maintenance?

Although there is a considerable budget for preventive maintenance, non was performed during our time frame. However, there were quite some breakdowns, with a widespread in duration:

OEE chart detailing on failures

This shows us the maintenance strategy needs to be reviewed and setup for a strong performance.

Making all losses visible

OEE Coach enables us to analyze and visualize each loss-category quick and easy. 

Managers, team-leaders and even operators can do this themselves!

We teach them to present facts and figures in their team meetings and at shift-end!

Visualizing and discussing the issues that hinder the effective use of the shift-time  fact based, allows them to cooperate in a focused way.

 

Conclusion 3: 
Finding the time to merge the two shifts can be done
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Performance and Quality Losses

What is the performance of the machine an what about the quality of its output?

Typically manufacturers have a high focus on downtime (availability) and consider the performance and quality as a given. Also here: Speed and quality -as often- wasn’t even taken into account in their OEE data.

In this step of the analysis we search and reveal: What makes the machine run slower than its theoretical maximum? Where does it loose expensive product due to quality problems?

Just one of the things we visualized is the enormous difference between the performance of different products.

How does the machine loose scheduled time? What makes it stop?

While OEE coach does the number crunching, every user immediately sees the differences between product A and B:

OEE product effectiveness 12

OEE product performance 13

In this factory 2% of the blisters are out of spec. And yet, it is not been taken into the OEE. The actual volume is so high there is even a de-blister machine!

Scrap, reduced speed and minor stops are often accepted as a fact of life. Showing the losses in a visual way makes people start thinking about it.

It is the behavior we want to change!

 

Conclusion 4: 
Reduced speed and minor stops eat away a substantial amount of capacity. And on top, 2% of the production needs to be de-blistered.

About the Analysis

The loss-analysis above and the financial analysis are made based upon the data provided by the customer.

Each activity at each moment of the day may have a different cost-price. The same to the output. OEE Coach takes all those parameters into account and calculates the correct P&L structure during the shift(s).

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The Financial Analysis

Every loss cost money. Every value created can be converted into money.

Our algorithm allocates costs and revenues to each individual datapoint.

Based on the actual OEE data, we can make current- and ‘What If’ analyses.

This means OEE Coach goes beyond OEE improvement. The system can also be used to provide operations management the necessary information to make capacity decisions.

The actual situation:

(In the financial analysis, the KPI values are slightly different due to a correction in the data in a later stage)

At this performance the product costs is 0,33€ per product and 10,4K value is generated per day:

OEE Actual cost structure

 

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Scenario 1

Simple improvements, to be done within 3 months:

  • No more un-scheduling during shift time
  • Reduce waiting time from 217 to 180 min
  • Reduce failures from 43 to 30 min

Result of scenario 1: Some simple improvements, to be realized within 3 months:

OEE Scenario1 KPI

In this easy to achieve scenario, the cost per product drops with 12% to 0,29€ and the daily created value goes up to 19K per day: leading to 2.2 Mio €/yr extra created value. A price drop of 12% provides you with a competitive edge to fill the extra capacity.

OEE cost scenario 1

 

Machine generates 8500€ per DAY more: in 260 working days/Yr

 

Improvement:

 

Cost per product -12%

Capacity +70%

Generates +2.2 Million€ per year

Double the capacity AND lower the cost

The challenge was to double the capacity and at the same time lower the cost.

Here there is just one scenario how to achieve this.

We make a detailed plan how to proceed, step by step.

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OEE Coach enables it!

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Scenario 2: Double the capacity

We simulated a scenario we know is very feasible:

  • No more un-scheduling during shift time
  • Reduce waiting time from 217 to 180 min
  • Reduce failures from 43 to 15 min
  • Improve actual speed from 48 to 55 blisters
  • Reduce rejects from 2 to 1%

Scenario 2 requires TPM/Lean/Monozukuri knowledge but can be well done within a year and yet leaves quite some room for further improvement:

OEE scenario 2 KPI

In this scenario the cost per product drops further to 0,27€ and the daily created value goes up to 23K per day: leading to 2.2 Mio €/yr extra created value.

 OEE scenario 2 cost

 

Machine generates 12.600€ per DAY more: in 260 working days/Yr 

Improvement:

 

Cost per product -18%

Capacity +101%

Generates +3.2 Million € per year

OEE Coach makes visible what others do not see.

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Let us Analyse your Potential!

What if there is a hidden machine behind your current one?

Before you think about capital investments, let us do the math!

You night be surprised about the Gold that is hidden in your facility…

 

Let us calculate your ROI?

Want to know how much potential we see?  Let us do the math!