{"id":14633,"date":"2026-04-29T07:25:56","date_gmt":"2026-04-29T05:25:56","guid":{"rendered":"https:\/\/optano.com\/?p=14633"},"modified":"2026-04-29T07:25:57","modified_gmt":"2026-04-29T05:25:57","slug":"insights-production-allocation-in-chemicals-and-pharmaceuticals","status":"publish","type":"post","link":"https:\/\/optano.com\/en\/media\/insight\/2\/insights-produktionsallokation-in-chemie-und-pharma\/","title":{"rendered":"Insights: Production allocation in chemicals and pharmaceuticals"},"content":{"rendered":"
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Production allocation in chemicals and pharmaceuticals<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Why Excel reaches its limits in multi-site planning <\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The bottleneck often begins unspectacularly. At location A, a line is tied up due to an ongoing campaign. Site B would still have free capacity, but some lines would have to be serviced and released again. At the same time, an important order is waiting, a raw material is late and a quality release is still pending. Everything is visible. And yet the central question remains: which site should produce what, in what order and under what conditions?<\/p>

Particularly in the chemical and pharmaceutical industries, cross-site production planning is not just a coordination problem. As soon as several plants are involved, it is not enough to simply shift quantities. Every relocation also changes cleaning effort, capacity utilization, material flows, releases, delivery capability and costs. Excel can document such correlations in production planning. However, it cannot reliably evaluate them at the same time.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u201eFree capacity is not yet a good decision.\u201c<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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An additional location does not automatically create more scope<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Several production sites initially act as a safety net. If there is a shortage at one plant, another is supposed to step in. However, this logic only works to a limited extent in the chemical and pharmaceutical industries. Not every plant is suitable for every product. Not every line is quickly available again. And not every decision can be made solely on the basis of free capacity. Quantity is often only the most visible factor, but not the decisive one.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The real effort is in the changes<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Many problems do not arise during stable production, but at the transitions. When is a change of location worthwhile? Which sequence reduces cleaning and changeover costs? Which additional batch shifts next week's schedule?<\/p>

In batch and campaign environments in particular, it is not only the quantity that determines a good plan, but also the sequence. An additional changeover can be more expensive than a supposedly less favorable location. This is precisely why table logics often fall short: they show quantities and dates, but not reliably the consequences of a change.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u201eSecurity of supply counts in pharma, campaign stability in chemistry.\u201c<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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In pharma, it's not just capacity that counts, but also release logic\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In the pharmaceutical industry, a production plan is only resilient if it makes sense not only in terms of capacity, but also in terms of quality. A batch that could theoretically be produced is not yet a reliably available contribution to supply. Quality testing, approval processes and site-specific requirements significantly change the operational logic.<\/p>

Multi-site planning in pharma is therefore more than just quantity distribution. It controls a system in which security of supply, regulatory requirements and production reality are closely linked.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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In the chemical industry, campaigns and costs make the decision more difficult\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The mechanism is different in the chemical industry, but the consequences are similar. Here, campaigns, product sequences, cleaning effort, energy consumption and stable plant occupancy characterize the planning. A site with free capacity is not automatically the better economic answer if this results in additional changes or unfavorable campaign lengths. High energy and feedstock costs increase this pressure.<\/p>

The real challenge therefore lies in deciding across all locations which occupancy is better under real restrictions. And this is where Excel's strength as a planning tool comes to an end: a lot becomes visible, but the overall system can only be reliably evaluated to a limited extent.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u201eOptimization not only changes the plan, but also the decision-making logic.\u201c<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The change of perspective starts with the network<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Mathematical optimization does not replace the experience of planners. It changes the structure of the decision. Instead of checking site by site which plant could still accommodate something, it evaluates the production network as an interconnected system. Capacities, product sequences, releases, material availability and conflicting objectives are considered together.<\/p>

This means that decisions no longer result from a series of local compromises, but from a consistent assessment of the overall system<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Conflicting objectives are explicitly<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In practice, the actual questions are rarely just: Where is there still capacity? More relevant is: Should a batch be relocated even though additional changes are required? Is a stable campaign more important than short-term flexibility? How much reserve makes sense when costs and delivery capacity are under pressure at the same time?<\/p>

Optimization makes such conflicting goals visible. It translates priorities into a reliable decision-making logic and shows which levers really work.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Further interesting content<\/p>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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