MANUFACTURING
Some of the pros and cons
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Currently, lateral-flow technology is core to many diagnostic products (Figure 1). With increasingly strong market competition there is a continual drive to minimise the cost of assembled goods while at the same time improve their quality. As a result, research and development groups are focussed on efficient development and are keen to ensure products move swiftly to market. In the late stages of development, companies often use manually operated pilot production lines with a contract manufacturer. The contractor’s range of generic manual processes can be quickly adapted to produce the initial low volumes that research and development groups require and is, therefore, a flexible cost-effective solution at this time in a product’s life cycle. As production volumes increase the flexible service being offered may no longer be a cost-effective solution.
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The manufacturing difficulties associated with lateral-flow assays are similar to those of other products. In addition, the core technology is considered to be mature. In attempts to meet new market demands the capabilities of lateral-flow devices are continually stretched and efforts to improve sensitivity and accuracy occupy many research and development groups. The resulting lateral-flow devices become more complicated with additional components being integrated to achieve the required “extra” functionality. As a result of this increased complexity, the overall reliability of the manually assembled devices begins to fall. Misalignment, poor tolerances, missing components, incorrectly assembled case parts and even material defects all add to the quality control burden. The resulting cost of assembled goods increases accordingly, as does the time it takes to manufacture them.
Contract manufacturers often supply services tailored to routine products. The capabilities offered are general and often limited, and any one single customer rarely drives a contractor’s expansion. Although a thorough review of the contract manufacturer can readily determine his/her capabilities and limitations, all too often the capabilities and production capacity are not scrutinised deeply enough.
Typically, successful products experience continued growth in the market place. As a company’s marketing group predicts growth, the capability and capacity offered by manual production lines cannot always keep up. Automated solutions exist, but when few companies have internal experience and external contract manufacturers do not have the capability, the route to volume production is complex.
The essentials of timing
Defining the point at which a company should move from a manual production line provided by a contract manufacturer is dependent on a number of critical pieces of information. Not all of this information is readily available, for example estimated market figures and forecasts, capital costs and the cost of goods. Contract manufacturers will undoubtedly provide convincing arguments justifying their capability. However, the correct choice of manufacturing route and knowledge of the critical decision points can save millions of dollars per year. Alternatively, delaying decisions on when to ramp up manufacturing can similarly cost millions of dollars per year in lost revenue. Ultimately, stakeholders will be required to authorise the purchase of capital equipment and these are the very people who need to clearly understand the available options.
The most important question that a company must determine is when should it increase its production capacity and move from a manual production process. A number of different manufacturing routes are available and their applicability differs from company to company and market to market.
Cost structuring
Cost modelling is not a new concept and is widely used across a number of industries. This approach allows for highly complex and interconnected data to be analysed simply. Applying cost modelling to the manufacture of medical devices provides a powerful tool to help achieve the cost and quality targets for which companies strive. One major benefit is that potential conflicts of interest can be avoided, because passionate issues are dealt with through data that can be presented logically and clearly.
By developing a structured cost model, based on a number of manufacturing scenarios (manual, semi-automation and fully automated), the merits of each scenario can be directly compared, which allows an optimum solution to be identified. This technique differs from traditional cost modelling because the manufacturing scenarios can be well defined with high quality technical input. This enables estimates for equipment and materials provided by third-party suppliers to be incorporated into each scenario and directly compared. This technical definition, together with an assessment of the required equipment for each of these scenarios, means that their relative merits can be accurately assessed. Once the cost model has been constructed and an optimum manufacturing scenario identified, minimal extra work is required to complete the definition of the manufacturing scenario using the existing technical definition.
Check the results
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Figure 2. [6] Structure of the cost model.
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As with any modelling, it is important to check the validity of the results. By using a parametric approach when constructing the model, critical data can be substituted to examine and understand the impact of certain assumptions, particularly because of missing data and delayed market growth. At this stage of model development, missing data can be assumed and subsequently alternative values used to test for sensitivity. Figure 2 [6] shows the architecture of a typical model. A number of inputs feed into the model, together with a set of manufacturing scenarios. The resulting output from the model is a trade-off analysis, as well as critical decision points and an idea of when those decisions need to be made. Ultimately, information required to support stakeholder decisions and an overall manufacturing plan can be extracted from the cost model.
Cost of each assembled device
Once the model is constructed and checked, the interdependencies between the data can be expressed in a number of ways. Interpretation of the results of the cost modelling should be made with caution. Because the data are highly complex and interconnected, trends, dependencies and results may at first be misleading. Care should be taken; those who are unfamiliar with this approach may incorrectly interpret the results. Only with a thorough technical understanding of the manufacturing scenarios, the critical data and the construction of the model is it possible to proceed with the analysis.
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Figure 3. [7] Effect of automation on the cost per device.
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First, the variability of the cost of assembled goods can be examined with differing production volumes. As illustrated by Figure 3 [7], often the cost per device produced on the manual production line is substantially lower than that for an automated line. However, by increasing the production volume it is quickly evident that as the amortisation of capital equipment is spread over a larger number of devices, the cost per device falls. This is also partly attributable to the reduced labour costs. Having assembled a comprehensive cost model, it is easy to determine what the cost of assembled devices provided by contract manufacturers should be. This can be useful to ensure that the contract manufacturer is supplying value for money.
Predict income
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Figure 4. [8] Revenue analysis resulting from cost modelling.
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With knowledge of the target retail cost of the device, the results from the model can be expressed as revenue to the company. By presenting data in this format the direct benefit of automation can be seen. In addition, predicted income forecasts can be useful for stakeholders. By considering the manual production process as a baseline, alternative manufacturing scenarios can be directly compared. This comparison results in the identification of an optimum point at which it becomes more profitable to move between production scenarios. This point is clearly illustrated in Figure 4 [8]. This optimum point defines when the fully qualified equipment needs to have been acquired, installed and validated. By interpreting the data in a slightly different way it also shows the impact of delaying the move to automation in terms of lost revenue, which is an equally convincing argument for change.
Timing of equipment acquisition
Not only will the cost model highlight the relative merits of different manufacturing scenarios with clarity, but it will also provide a solid foundation for planning. To realise the savings predicted by the cost modelling approach, a move to automation will undoubtedly be required, providing volumes are high enough. Automation equipment usually has a significant lead time, often similar to the development time of the product. A thorough understanding of when this equipment needs to be specified, ordered, installed and qualified is vital to being able to achieve significant cost savings and ensure that the manufacturing of products is as efficient as possible. The output from the model allows for focussed discussions with equipment suppliers at an early stage of an automation programme. This helps to reduce potential difficulties with design and installation of the equipment and to reduce the duration of the programme. These discussions with suppliers allow likely timings for capital expenditure to be established and fed into the cost model and planning. Making stakeholders aware of financial commitments will help to reduce delays to the programme.
The acquisition of automation equipment is not a trivial activity because large capital expenditure requires justification and is usually an emotive subject. Rarely is the decision easy and often missing information can lead to paralysis in decision-making.
Avoid delays
Cost modelling should be an intrinsic part of plans to ramp up to volume manufacturing. It provides critical analysis and helps prevent decision paralysis. This approach is not simply a financial planning tool. By constructing a clear and definitive cost model that is based on high quality technical information, stakeholders can be provided with strategic information. Important decision points, capital expenditure and revenue plans can all be determined. Alternative manufacturing scenarios can be readily defined and assessed, and the right decision for each company can be made. Ultimately, failure to understand and perform a thorough assessment of the manufacturing scenarios using cost modelling tools will lead to inevitable delays, lost revenue and lost opportunities.
Simon Burnell is Head of Diagnostics at Cambridge Consultants Ltd, Science Park, Milton Road, Cambridge CB4 0DW, UK,
tel. +44 1223 420 024, e-mail: simon.burnell@cambridgeconsultants.com [9] www.cambridgeconsultants.com [10]