{"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-into-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 Chemistry 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 by an ongoing campaign. Location B would still have free capacity, but some systems would need to be maintained and released again. At the same time, an important order is pending, a raw material is delayed, and a quality release is still outstanding. Everything is visible. And yet, the central question remains: which location should produce what, in what order, and under what conditions?<\/p>

Especially in chemistry and pharmaceuticals, cross-site production planning is not just a coordination problem. As soon as multiple plants are involved, simply shifting quantities is not sufficient. Every transfer also changes cleaning effort, capacity utilization, material flows, releases, delivery capability, and costs. Excel can document such interdependencies in production planning. However, it cannot reliably evaluate them simultaneously.<\/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 doesn't automatically create more leeway.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Multiple production sites seem like a safety net at first glance. If one plant gets overwhelmed, 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 based on spare capacity. Quantity is often only the most visible, but not the decisive factor.<\/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 lies 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 arise not during stable production, but at the transitions. When is a change of location worthwhile? Which sequence reduces cleaning and setup effort? Which additional batch shifts next week's schedule?<\/p>

Especially in batch and campaign environments, not only the quantity but also the sequence determines a good plan. 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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\u201eIn pharma, supply security counts; in chemistry, campaign stability.\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 the 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 reliable when it is not only capacity-wise but also quality-wise sensible. A batch that could theoretically be produced is not yet a reliably available contribution to supply. Quality control, release processes, and site-specific requirements significantly alter the operational logic.<\/p>

Multi-site planning in pharma is therefore more than just volume distribution. It manages a system in which supply security, regulatory requirements, and production reality are closely intertwined.<\/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 chemistry, campaigns and costs intensify the decision.\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In chemistry, the mechanism looks different, but the consequence is similar. Here, campaigns, product sequences, cleaning effort, energy consumption, and stable plant utilization shape the planning. A site with free capacity is not automatically the more economical answer if it leads to additional changeovers or unfavorable campaign lengths. High energy and feedstock costs intensify this pressure.<\/p>

The real challenge, therefore, lies in deciding across locations which assignment is better under real-world constraints. And that is precisely where Excel's strength as a planning tool ends: many things become 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 changes not just the plan, but the decision 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 in perspective begins 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 decision-making. Instead of examining location by location to see which plant could still absorb something, it evaluates the production network as a connected system. Capacities, product sequences, releases, material availability, and conflicting goals are considered together.<\/p>

This means decisions are no longer made from a series of local compromises, but from a consistent evaluation 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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Goal conflicts are explicit<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In practice, the real questions are rarely just: \"Where is there still capacity?\" More relevant are: \"Should a batch be relocated even if additional changeovers are incurred there?\" \"Is a stable campaign more important than short-term flexibility?\" \"How much reserve makes sense when costs and delivery capability are under pressure at the same time?\"<\/p>

Optimization makes such conflicting objectives visible. It translates priorities into a robust decision-making logic and shows which levers actually have an effect.<\/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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