With the development of large-scale lean manufacturing, there are more and more small-batch multi-batch orders, and order management is becoming more and more complicated. Before the start of production, order distribution is the first hurdle, especially for enterprises with multi-factory production mode, order distribution has a greater impact on production and delivery efficiency, and different distribution methods will also lead to significant cost differences.
The traditional suborder mode usually relies on manual decision-making or follows a fixed standardized mode. The suborder efficiency is low, and it is difficult to fully consider all factors, resulting in a large amount of production resources and cost waste. So how do enterprises achieve sub-order optimization?
Before analyzing the solution path, let’s take a look at the difficulties of multi-factory distribution. I believe that each enterprise in the sub-order, will consider the three issues: delivery, production capacity and income, strictly speaking, they are very important, but each enterprise is different, the priority of consideration is not the same, often there will be a situation.
At the same time, due to technical limitations, it is a great challenge for enterprises to calculate all the factors of each problem. Whether it is delivery time, production capacity or revenue, they are not just a single dimension of the problem, they are interrelated and impact, how to systematically comb and quantify these impact factors is also a huge challenge. Especially for those large enterprises whose production may involve hundreds of factories, thousands of workshops and production lines in different regions, the difficulty of single division is self-evident.

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Second, the factory capacity matching is not reasonable, resulting in a waste of resources and costs. The quantity of products ordered is more or less, the capacity of the factory is large or small, they are not necessarily one-to-one correspondence, some orders need to specify the factory, and some factories can undertake the output of several orders at the same time. For example, if there are 10 factories that can be produced for a certain batch of orders, in fact, 10 factories will not be allowed to produce, and some factories have a relatively large capacity and can undertake the production of 5 orders, and enterprises can have more choices when ordering. In standardized mass production, usually the more the number of production, the lower the cost, the factory opens a machine production, if you can produce as much as possible, you can reduce the loss of machine operation.

Intelligent decision making is a process in which an organization or individual makes comprehensive use of a variety of intelligent technologies and tools to model, analyze and make decisions on relevant data based on established goals. The process synthesizes constraints, strategies, preferences, uncertainties and other factors, and can automatically achieve the optimal decision to solve the increasingly complex production and life problems in the new growth era.

In the intelligent manufacturing decision optimization platform built by Shanshu Technology – Shanshu digital Yi, the demand distribution table can realize the intelligent upgrade of multi-factory orders. The system will model the factory data, distribution rules and business requirements according to the business characteristics of the enterprise. After the input of the order data, the system can automatically consider the order delivery time, cost, income, etc., with the goal of maximizing revenue, solve the order efficiently through COPT solver, match the order with the production capacity of different factories, and output the optimal distribution result.

In the specific sub-order process, enterprises may have multiple demands, such as the lowest cost, the latest delivery time, the least number of factories, etc. In the system, enterprises can flexibly adjust the model and parameters according to different needs, output different versions of the sub-order results, and better sub-order optimization through comparison. For example, the delivery time of a batch of orders is 2 months, and the enterprise can set the delivery time of 2 months and less than 5 factories as constraints to get the lowest cost suborder plan; We can also set the delivery time of one and a half months and the constraint of less than 10 factories to get the lowest cost suborder plan. By comparing different distribution plans, companies can make more informed decisions based on specific circumstances.

Compared with the traditional way, the sub-order mode based on intelligent decision-making breaks through the limitations of human work sub-order in the efficiency of sub-order, can quickly respond to order changes, and meet the sub-order needs of enterprises under different business objectives. In terms of the suborder effect, the global decision-making is more scientific and economic, laying a solid foundation for the follow-up production execution.