The industrial manufacturing process is complex, the link is long, the influencing factors are many, many enterprises in the pursuit of scale efficiency, easy to fall into the trap of false growth. For example, only considering the order, ignoring the research and development and supply capacity, although the order volume has soared, it has brought a variety of problems to the back-end production, materials, transportation and other links, resulting in an increase in performance costs, and entering the cycle of growth without profit.

This is essentially the performance of the imbalance of production, supply and marketing, in modern production and manufacturing, equipment, personnel, materials, orders and other factors bear a large amount of data, and have great instability, to weigh decisions in many unstable factors, the enterprise’s comprehensive operation management ability is a great test.

From paper, excel tables to digital systems, industrial production and operation management has been upgraded, but there is no breakthrough in essence, but the traditional operation model is moved to the online integration, just like “old wine in a new bottle”.

With the development of a new generation of intelligent decision-making technology, the calculation of billions of data is no longer a problem, and the thinking and mode of operations management are changing. The practice of advanced enterprises shows that intelligent decision-making can help enterprises simplify operation management problems, quantify and visualize dynamic, diverse and large-scale change elements with the thinking of operational research optimization, help enterprises find real high-quality demand, and promote the efficient execution and delivery of orders, and help enterprises achieve high-quality growth.

The essence of manufacturing operation management: revenue optimization under multiple objectives and constraints

Like all industries, the core purpose of manufacturing industry is to achieve economic value, and managers must calculate the “economic account” to ensure stable operation. As the modern manufacturing industry is moving towards lean and personalized, the demand for “multi-batch small batch” is increasing, and the order-driven production supply has become the trend.

And an order from the order, distribution, procurement, production, shipping to delivery, to go through “layers of checkpoints”, when countless changes in the order intertwined, operation management needs to consider the factors will be very complex.

At the planning level, enterprises should comprehensively consider all production factors and carry out macro-control on the overall production capacity, income and material supply. At the planning level, it is necessary to consider all order constraints (income, delivery time, materials, personnel, etc.), arrange better production cycle and resources for each order, and dispatch procurement, shipping and other departments to provide relevant support according to the plan; At the execution level, production resources should be reasonably arranged for specific orders, and resource utilization and business income should be improved while meeting the delivery date. In actual production, planning, planning and execution are trinity, planner and planner can not ignore the differentiated impact of each link, the executor can not only see a single order or element.

From a technical point of view, this is actually a revenue optimization problem under multiple objectives and multiple constraints.

Under the traditional operation management model, due to technical constraints, demand, production and supply are relatively separated, many production factors can not be quantified, and it is difficult for enterprises to take all factors into account when making decisions. Orders are basically managed and delivered in accordance with the standardized “one-size-fits-all” mode, and it is impossible to carry out fine management of different orders.

The breakthrough of intelligent decision-making on production and operation management is reflected in three aspects. First, it solves the problem of large-scale computing, allowing enterprises to comprehensively consider the impact of various factors on business income from different angles; Secondly, the information gap between different departments is broken in the process to achieve unity and coordination from planning to implementation; Third, let enterprises carry out differentiated management and optimization of each module from a global perspective to achieve refined changes in operation management.