This article will discuss opportunities to improve the efficiency of cobalt-60 (Co-60) utilization within a gamma irradiator. It will show how redistributing the Co-60 within the source rack may lead to improved throughput or dose uniformity within a product. It presents examples of modifications to the equipment within the source pass; these include reduction in the carrier wall thickness and changes to the product stack size. It will discuss the process of scheduling and present ideas of how to optimize both the order of the products and transitions between the products to maximize process efficiencies.
Gamma irradiators, employing cobalt-60 (Co-60) as a radiation source, have been used for more than 50 years to sterilize medical devices. Approximately 40% of single-use medical devices are sterilized using gamma irradiation.1 One of the main objectives for most gamma irradiators is to process as large a volume of as many different types of products as possible, while safely achieving the dose requirements of the product. Improving the efficiency of the gamma irradiation process allows more products to be irradiated with the same amount of Co-60. This is especially important as many gamma irradiators are near design capacity and there is a high demand for sterilization services.
A gamma irradiator comprises three main components, each of which can be optimized:
Product container (tote, carrier, pallet)
Product irradiation path
An example of a gamma irradiator is provided in Figure 1.
Gamma irradiators must consider efficiency in many areas, such as cobalt efficiency, packing efficiency, and scheduling efficiency. Each of these poses its own challenges and requires operational changes to achieve, but in the case of most gamma irradiators there is room to increase efficiency in at least one of these areas. This article will discuss each area and approximate the impact to the gamma irradiator performance.
Gamma irradiators employ two main designs:
Product overlap machines have product stacks that are taller than the source rack. That is, the product stack begins below the bottom of the source rack and ends above the top of the source rack. This design is the most efficient use of the radiation source as the source is almost entirely surrounded by the products.
Source overlap machines use source racks taller than the product stacks. That is, the product stack begins above the bottom of the source rack and ends below the top of the source rack. The source overlap design has advantages, such as ease of scheduling and changing of the product stack size to meet product uniformity requirements. However, cobalt efficiency is sacrificed. Figure 2 shows a comparison of the two designs.
The Co-60 sources are the engine of the gamma irradiator. In the gamma irradiation process, the sources are contained in a simple mechanical device, called a source rack, that needs little adjustment while in operation. However, the location of the Co-60 sources within the rack is critical. Co-60 decays at a rate of approximately 12% per year, requiring gamma irradiators to add new Co-60 sources on a regular basis, usually annually. These sources should not be randomly placed within the source rack as the location directly impacts shape of the radiation field. That is, the placement of the Co-60 sources defines the locations of the minimum and the maximum activity and thus the locations of the minimum and maximum dose within the product.
For example, consider a newly installed (less than 50% full of Co-60 sources) gamma irradiator of product overlap design. If 100 sources are installed in a configuration that provides the gamma irradiator with its best balance of throughput and dose uniformity within the product, we approximate a 7% increase in product throughput and a 4% improvement in dose uniformity within the product (using 0.1 g/cc product, based on mathematical modeling*) vs. installation in a randomly distributed fashion (i.e., sources and activities evenly spaced out throughout the rack).
Now, let us consider a mature (over 50% full of Co-60 sources) source overlap gamma irradiator and perform the same calculation as above. In this case, we see a 5% decrease in throughput using the optimal source arrangement vs. a random distribution. This may seem counterintuitive; however; there is an 18% improvement in dose uniformity within the product using the optimal source configuration (using 0.1 g/cc product, based on mathematical modeling).
The definition of “optimal” clearly depends on your objectives. As in the examples above, the source overlap could rearrange the Co-60 sources to achieve a higher throughput. However, the resulting large negative impact this would have on dose uniformity to the product is undesirable and, in most cases, prevents most products from being irradiated. The optimal locations of the cobalt sources are either determined through experiment (experience) or can be predicted through mathematical modeling.
To calculate the possible dose distributions within a given product, and thus throughput and dose uniformity within the product, mathematical modeling can be used. Using a “design of experiments” (DoE) methodology, many cases can be tested and sorted to determine the optimal case for a given gamma irradiator.
The most common design to hold Co-60 sources is a planar source rack. This rack is made up of rows and columns. To create a DoE for this type of source design, the amount of cobalt in each given region (module) is defined. The activity in a given row or column is defined by the percent of total activity. The amount of activity in a given module is the percent activity in the row multiplied by the percent activity in a column. To create the DoE, the amount of activity in each row is varied and the throughput and dose uniformity within the product (dose uniformity ratio; DUR) is calculated. The results can then be sorted to determine the optimal activity distribution in each module. Once the optimal distribution is determined, this can be used as an input to plan the Co-60 source installation.
Figure 3 shows a generalized example of a DoE where each row, R, is varied (R-xy – R-xy), where x is the experiment number and y is the row number. For example, R-46 is the amount of activity in row 6 in experiment 4. This exercise can be repeated for each column as well. For scale, there can be thousands of experiments that need to be run (i.e., there are thousands of possible combinations of how to distribute the cobalt within the rack). There are even more possible combinations if we do not first limit to pragmatic distributions.
Product Container Efficiency
The product container transports the product from the storage area into the source pass. There are three common containers:
Tote—Usually an aluminum or cardboard box that sits on a conveyor and is pushed into the source pass (Figure 4).
Carrier—An aluminum box, larger than a tote, that hangs from an overhead rail and has a keel on the bottom (Figure 5). This rail is used to guide the carrier into the source pass, where the carrier bottom is secured into a keel guide.
Pallet—Used for standard U.S. or European pallets where the product is stacked and secured, often with shrink wrap. The pallet is placed onto a slave pallet, which is on a conveyor. The slave pallet guides the product along the irradiation path (Figure 6).
Each of the containers ensures that the product is placed into a reproducible position relative to the source rack. Given that the product container guides the product, any modification to the container has an influence on the dose to the product.
The product container places the product within the source pass (Figure 1). Modifying the position of the product container requires substantial effort but has a large influence on the dose rate and dose uniformity within the product.
In general, dose uniformity degrades as you move closer to the source rack, as variation in the individual Co-60 sources and product placement becomes more evident. Likewise, moving the product away from the sources smooths out any variations, allows a more uniform radiation field, and improves dose uniformity within the product.
However, the opposite is true with the dose rate: As you move closer to the source, the radiation field becomes more intense. The higher dose rate allows the product to reach its minimum required dose faster, resulting in more products moving through the gamma irradiator (i.e., higher throughput). Figure 7 shows that as the product is moved further away from the rack (to the right on the x-axis), the throughput (blue) drops. It also shows that the uniformity (red); that is, the dose distribution within the product gets smaller, meaning more uniform.
Product Overlap vs. Source Overlap
The product overlap design uses Co-60 more efficiently; however, in general, optimizing the order of the product to be irradiated is more difficult with this design. The source overlap design is more flexible regarding the order in which products can be irradiated. Each of these designs can be seen in Figure 2.
A mathematical model was created for each design type (product overlap vs. source overlap) with equal Co-60 activity; each was deemed to have an optimal Co-60 distribution. For all common product densities used in gamma irradiators, the product overlap design was calculated to be approximately twice as efficient in terms of throughput and provide 3%–15% better uniformity, for densities 0.1–0.4 g/cc, respectively.
However, to achieve these gains, the source pass equipment must be replaced. This means that the single-level product container (typically a hanging carrier) must be removed or modified to have two levels. For example, a shelf could be added to the carrier. Then, a product interchange would need to be added to move the product between the top and bottom levels. A new installation qualification, operation qualification, and performance qualification (PQ) need to be completed after a modification of this magnitude. This includes determining new product load configurations throughout the PQ process. While large gains in performance could be achieved, the cost and time lost for the work would be significant.
Most gamma irradiators operate through a “shuffle and dwell” design, meaning the product container dwells (is stationary) in one position for a given time and then shuffles to the next location. The cycle time equals the total amount of time needed for a product container to shuffle and dwell. This means that the cycle time has a mechanical limitation (lower limit) for how long it takes for all of the shuffling to happen within the source pass.
Mechanical limitations occur in two cases:
The gamma irradiator must be run quickly to meet product requirements. This can occur when products with a lower dose specification need to be irradiated in a system with a higher dose rate.
Incremental dose—Some gamma irradiators cycle the product through the process (through all dwell positions) multiple times. This allows the operator to schedule low-dose products with high-dose products and reduce the number of transition products required. See Process Scheduling section below for more information.
Examples of current approaches to overcome mechanical limitations by modifying the process include setting the target dose of the product higher than its required minimum and lowering one of the racks holding the sources to effectively lower the amount of activity in the gamma irradiator. Both of these approaches solve the mechanical limitation problem but reduce the gamma irradiator's efficiency.
Mechanical limitations can also be overcome by modifying the equipment (e.g., by replacing old pneumatic drives with newer electric drives). Electric drives are more consistent than pneumatic drives, resulting in shorter and more predictable cycles. Additionally, electric drives require substantially less maintenance, which reduces the overall downtime of the gamma irradiator, thereby increasing overall efficiency.
In some cases, product flow (the shuffle time within the source pass) is the limiting factor of the cycle time. For example, gamma irradiators that transport product on a monorail (i.e., hanging systems) may use an inefficient process flow that slows down to allow products to move between rows within the source pass.
An example of removing a monorail and replacing it with a cross-transfer is shown in Figure 8. Here, the monorail was used to move the product into and out of the cell. However, this is slow. This bottleneck can be replaced with cross-transfers that allow a more efficient movement of the product container and allow the overall process to move faster. In Figure 8, we can see that the cross-transfer drops off to a different lane between product inlet/outlet. This allows product to be more efficiently staged to enter the gamma irradiator. Also, the cross-transfer can move faster than the product container hanging on the monorail. In past projects, we have seen up to a 30% reduction in minimum cycle time by employing this approach.
Another design bottleneck can occur in the interim (maze) product flow. In some designs, the incoming products and the outgoing products share the same path. This requires the incoming product to wait for the outgoing product to exit before it can enter. This limitation can be overcome by modifying the product flow in the interim area to add a second level. This will allow the products to flow over/under each other at the same time, removing the requirement to wait for other products to move. Alternatively, more temporary hold points can be created in order to reduce the bottleneck.
Product Stack Height
Adding a larger product stack will allow more products to move through the irradiator. However, the length and width of the product stack are limited by the movements through the irradiator. Adding a tall stack may be possible in the case of carriers and pallets, if space permits. In the case of carriers, this may require the adjustment of shelf locations. In the case of pallets, a taller stack may be possible.
A more ambitious approach is to move the conveyors. In most two-level pallet gamma irradiators, it is possible to lower the bottom conveyor to increase the product stack height. In our calculations, we have estimated up to a 20% increase in product throughput and an improvement of nearly 10% in dose uniformity by increasing the product stack by 12″ (i.e., by lowering the conveyor by 12″ to accommodate a larger product stack).
The walls of the product container, while necessary for mechanical stability, attenuate gamma radiation. Many carrier designs use walls that are 1/8″ thick. However, we have found that carriers of 1/16″ thickness can be used in the field without significantly more wear-and-tear. Using mathematical modeling, we predict that removing 1/16″ from the wall thickness results in a gain of approximately 3% in throughput, with little effect to the dose uniformity within the product.
Process scheduling is the organization and selection of products that enter the gamma irradiator and, most importantly, in which order. This is critical to the efficient operation of a gamma irradiator as the products within the source pass interact with each other. The interaction can happen by shielding between product containers in different rows—as in the case of a multi-pass machine—or between neighboring product containers, as it can allow scattering of the gamma radiation.
To mitigate these interaction effects, a gamma irradiator site must determine which products are compatible with each other. That is, which product can be run before and/or after other any given product while still meeting the product dose requirements? This compatibility is usually determined through trial and error experiment using dosimeters to measure the impact of leading and trailing product.
Once each product's compatibility relative to other products is determined, a schedule of the order of products to be irradiated can be created. To make this process more efficient, groupings—often called “processing categories”—can be used. These processing categories can be sorted by density and dose requirements. This reduces the required number of experiments necessary to determine compatibility, thereby simplifying the scheduling process.
Once this list of compatibilities is created, the scheduler of the gamma irradiator must establish the order of products to irradiate based upon the products that become available (i.e., the schedule). In the case of in-house gamma irradiators, this may be straightforward. There may be only a few processing categories, which do not change often, and timing of product arrival at the gamma irradiator may be predictable. However, contract gamma irradiation facilities have a more difficult time. Their customers (and thus the available products list) typically flow day-to-day or even hour-to-hour, and they must adjust their product schedule often, sometimes more than once a day.
The constantly changing list of available products requires a lot of planning effort, and available products may not all be visible to the scheduler at the time of schedule creation. This often requires the scheduler to work with incompatible processing categories.
When the only available products are incompatible, the gamma irradiation source pass must be flushed. I.e., many product containers full of transition product—which may be filler or dunnage—or empty containers must be used. Transition production, particularly “empties,” are normally of low or no value to the gamma irradiator facility.
This transition product can have a large effect on the efficiency of a gamma irradiator. A typical gamma irradiator loses 5%–15% of its throughput due to scheduling inefficiency. The best way to reduce the amount of transition time is to use a scheduler with many years of experience, who has determined the optimum setup rules and who executes to those rules perfectly every time. As the number of products and dose ranges increase, optimal scheduling becomes nearly impossible for a person to accomplish. The only way to guarantee optimal scheduling is to automate the scheduling process. An automated scheduling process would have access to all of the available products and rules, allowing it to optimally sort the products to reduce the required transition phases.
A further optimization to the scheduling process is to reduce the required amount of experiments to determine compatibility. This can be accomplished through a validated mathematical model that imports the product geometries, material, and dose requirements. The compatibility experiments can then be run virtually and used to create the rules that are fed back to the scheduler.
Combining an automated scheduler and mathematical modeling would allow nearly real-time addition of new products to the gamma irradiation process.
This article has outlined many areas of possible improvement in the efficiency of gamma irradiators. Some of these may be straightforward to implement, while others would be a significant investment in time and cost. The performance due to modifications in each of these areas is dependent on the design of each irradiator and the product that is being irradiated.
All of the situations discussed present ideas to improve the gamma irradiation process. However, it should be noted that any change may have a tradeoff that should be considered. For example, if a product container is made too thin, wear-and-tear will become a problem; rearranging the cobalt distribution may improve the throughput but will usually negatively impact the product dose uniformity; and more efficient scheduling is less versatile (cannot react easily to quick turnaround products).
Table 1 presents an overview of the results of this article for the potential increase in performance. However, it should be cautioned that throughput is negatively correlated with dose uniformity. That is, an improvement in throughput often results in degraded dose uniformity.
To put some of the results into perspective, a mid-size gamma irradiator could have 3 MCi. A site that is able to improve its efficiency by 3% could process the same amount of material while saving 90,000 Ci. Another way to see the gains would be to look at a 4-pass carrier design with 3 MCi, which can process approximately 700,000 cubic feet of material per year. An efficiency gain of 3% means that it can process an extra 21,000 cubic feet per year, which yields an extra 1,700 carriers per year.
The author thanks the Nordion Engineering Team for helping to identify examples to be included based on past work, and for reading this article to ensure accuracy and consistency. The author also thanks the Nordion Design Office for creating great figures on short notice.
In the context of this article, mathematical modeling is the creation of a virtual representation of the gamma irradiator using a computer program. This includes the product container geometry and materials, the Co-60 activities and locations, and an approximation of the product.
The geometry for the models used in this article was constructed based on Nordion engineering drawings and the results were calculated using point-kernel methodology, following the guidelines in the industry standard.2 Due to the limitation of the point-kernel approach, all products and absorbers were approximated as rectangular cuboids, constructed of homogenous material, and the product stack had density no greater than 0.4 g/cc.
For the cases modeled in this article, all models were validated by comparing model results to data from existing Nordion-built gamma irradiators. The validation used data from the operation qualification—which uses 0.01–0.4 g/cc homogenous product—and followed ISO/ASTM 52303.3