Tackle Quality Issues and Improve OEE in Vision Systems for Packaging

Packaging industries must operate with the highest standards of quality and productivity. Overall Equipment Effectiveness (OEE) is a scoring system widely used to track production processes in packaging. An OEE score is calculated using data specifying quality (percent of good parts), performance (performance of nominal speed) and equipment availability (percent of planned uptime).

Quality issues can directly impact the customer, so it is essential to have processes in place to ensure the product is safe to use and appropriately labeled before it ships out. Additionally, defects to the packaging like dents, scratches and inadequate labeling can affect customer confidence in a product and their willingness to buy it at the store. Issues with quality can lead to unplanned downtime, waste and loss of productivity, affecting all three metrics of the OEE score.

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Traditionally, visual inspections and packaging line audits have been used to monitor quality, however, this labor can be challenging in high volume applications. Sensing solutions can be used to partly automate the process, but complex demands, including multiple package formats and product formulas in the same line, require the flexibility that machine vision offers. Machine vision is also a vital component in adding traceability down to the unit in case a quality defect or product recall does occur.

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Vision systems can increase productivity in a packaging line by reducing the amount of planned and unplanned downtime for manual quality inspection. Vision can be reliably used to detect quality defects as soon as they happen. With this information, a company can make educated improvements to the equipment to improve repeatability and OEE and ensure that no defective product reaches the customers’ hands.

Some vision applications for quality assurance in packaging include:

  • Label inspection (presence, integrity, print quality, OCV/OCR)
    • Check that a label is in place, lined up correctly and free of scratches and tears. Ensure that any printed graphics, codes and text are legible and printed with the expected quality. Use a combination of OCR (Optical Character Recognition) to read a lot number, expiration date or product information, and then OCV (Optical Character Verification) to ensure legibility.
  • Primary and secondary packaging inspection for dents and damage
    Inspect bottles, cans and boxes to make sure that their geometry has not been altered during the manufacturing process. For example, check that a bottle rim is circular and has not been crushed so that the bottle cap can be put on after filling with product.
  • Safety seal/cap presence and position verification
    Verifying that a cap and/or seal has been placed correctly on a bottle, and/or that the container being used is the correct one for the formula / product being manufactured.
  • Product position verification in packages with multiple items
    In packages of solids, making sure they have been filled adequately and in the correct sequence. In pharmaceutical industries, this can be used to check that blister packs have a pill in each space, and in food industries to ensure that the correct food item is placed in each space of the package.
  • Certification of proper liquid level in containers
    For applications in which it can’t be done reliably with traditional sensing technologies, vision systems can be used to ensure that a bottle has been filled to its nominal volume.

The flexibility of vision systems allows for addressing these complex applications and many more with a well-designed vision solution.

For more information on Balluff vision solutions and applications, visit www.balluff.com.

Operational Excellence – How Can We Apply Best Practices Within the Weld Shop?

Reducing manufacturing costs is absolutely a priority within the automotive manufacturing industry. To help reduce costs there has been and continues to be pressure to lower MRO costs on high volume consumables such as inductive proximity sensors.

Traditionally within the MRO community, the strategy has been to drive down the unit cost of components from their suppliers year over year to ensure reduce costs as much as possible. Of course, cost optimization is important and should continue to be, but factors other than unit cost should be considered. Let’s explore some of these as it would apply to inductive proximity sensors in the weld shop.

Due to the aggressive manufacturing environment within weld cell, devices such as inductive proximity sensors are subjected to a variety of hostile factors such as high temperature, impact damage, high EMF (electromagnetic fields) and weld spatter. All of these factors drastically reduce the life of these devices.

There are  manufacturing costs associated with a failed device well beyond that of the unit cost of the device itself. These real costs can be and are reflected in incremental premium costs such as increased downtime (both planned and unplanned),  poor asset allocation, indirect inventory, expedited freight, outsourcing costs, overtime, increased manpower, higher scrap levels, and sorting & rework costs. All of these factors negatively affect a facility’s Overall Equipment Effectiveness (OEE).

Root Cause

In selection of inductive proximity sensors for the weld manufacturing environment there are root cause misconceptions and poor responses to the problem. Responses include: leave the sensor, mounting and cable selection up to the machine builder; bypass the failed sensor and keep running production until the failed device can be replaced; install multiple vending machines in the plant to provide easier access to spare parts (replace sensors often to reduce unplanned downtime);  and the sensors are going to fail anyway so just buy the cheapest device possible.

None of these address the root cause of the failure. They mask the root cause and exacerbate the scheduled and unscheduled downtime or can cause serious part contamination issues down stream, resulting in enormous penalties from their customer.

So, how can we implement a countermeasure to help us drive out these expensive operating costs?

  • Sensor Mounting – Utilize a fixed mounting system that will allow a proximity sensor to slide into perfect mounting position with a positive stop to prevent the device from being over extended and being struck by the work piece. This mounting system should have a weld spatter protective coating to reduce the adherence of weld spatter. This will also provide extra impact protection and a thermal barrier to further assist in protecting the sensing device asset.
  • The Sensor – Utilize a robust fully weld protective coated stainless steel body and face proximity sensor. For applications with the sensor in an “on state” during the weld cycle and/or to detect non-ferrous utilize a proper weld protective coated Factor 1 (F1) device.
  • Cabling – A standard cable will not withstand a weld environment such as MIG welding. Even a cable with protective tubing can have open areas vulnerable for weld berries to land and cause burn through on the cables resulting in a dead short. A proper weld sensor cord set with protective coating on the lock nut, high temp rated and weld resistant overmold to a weld resistant jacketed cable should be used.

By implementing a weld best practice total solution as described above, you will realize significant increases in your facilities OEE contributing to the profitability and sustainability of your organization.

Ask these 3 simple questions:

1) What is the frequency of failure

2) What is the Mean Time To Repair (MTTR)

3) What is the cost per minute of downtime.

Once you have that information you will know with your own metrics  what the problem is costing your facility by day/month/year. You may be surprised to see how much of a financial burden these issues are costing you. Investing in the correct best practice assets will allow you to realize immediate results to boost your company OEE.