What are the main difficulties in APS implementation? As one of the core industrial software systems, APS has moved from being avoided by enterprises to being actively accepted. It is no longer necessary to deliberately persuade enterprises about the benefits of APS or why they should adopt it, because enterprises are already actively raising such needs themselves. So what problems are faced in actual implementation?

(1) Data Barriers

Compared with MES, APS has much higher requirements for data accuracy and completeness.

First is basic labor-hour data. This data should be accurate, but for quite a large number of enterprises it is completely inaccurate. Many MES systems that have already been implemented or even put into use could have gradually and iteratively collected accurate labor-hour data through effective standardized operation, but a considerable number of MES systems simply cannot or have not done so. In view of this, whether accurate actual labor-hour data can be accumulated should be seriously and formally proposed as an evaluation indicator for MES systems.

Process and resource data. APS needs structured processes. This is an obvious obstacle, but it is actually not too hard to solve. APS operation requires room for optimization, and it is necessary to establish matching set relationships between processes and resources, which is a fairly massive workload for some enterprises.

(2) Management Barriers

APS requires a very high level of management granularity, down to the process-operation level and machine-equipment level. Under traditional manual models, rough management at the workshop or work-section level, as well as secondary dispatching methods, is actually in conflict with APS's idea of comprehensive and unified optimized resource allocation.

For example, when planning involves multiple workshops, many enterprises simply throw tasks to workshops and tell them to complete them within a few days. This approach is fine when delivery schedules are not tight or capacity is sufficient, but many enterprises are not in that situation.

For example, many enterprises may only be able to manage at the day level. Each person or each workshop completes a designated task package every day, all handovers are arranged at night or in the morning, and no process connection between order operations is involved within the same day. This approach is actually a simplification of management and an expedient measure in the absence of tools. But it is likewise unsuitable when delivery deadlines are tight.

For example, in production preparation. Due to the lack of fine-grained operational planning guidance and pull, production preparation in terms of 5M1E is done far in advance and is actually very conservative. Otherwise, planning and scheduling personnel would not be like firefighters, spending a great deal of effort coordinating various production-preparation matters.

(3) Cognitive Barriers

For enterprises with relatively standardized management, MES systems are to a large extent a computerization of their existing management model. Although some methods can be introduced to bring out the advantages of digitalization, that is still its essential nature. But frankly speaking, APS represents a much more obvious step-up for enterprises.

Enterprises' existing planning models, especially under manual approaches, actually contain many irrational elements. Building an APS system on top of these irrationalities, or even fully copying them into computerized form, is likewise unreasonable. At the same time, the backend technology involved in this approach is generally not simpler but more complex, yet fundamentally it does not solve the problem. This is very frustrating. Enterprises must make certain changes in understanding.

For example, in many cases an enterprise's existing planning model has multiple planners and schedulers each responsible for scheduling different tasks. But for APS, all tasks and all resources are optimized in a unified manner. Because APS is collaborative in essence, the overall job scheduling scheme is affected everywhere once one part moves, which requires this collaboration to be built into the underlying computational logic of APS. In fact, this also changes the existing so-called collaborative model among planning personnel.

For example, many enterprise workshops use a two-level scheduling method for job scheduling, with team leaders and section chiefs being the actual operators who arrange work plans. But the drawbacks of this approach are very obvious. The frequent phenomenon in enterprises where what should be done is not done while a lot of work that should not be done gets done is caused by this. APS implementation is meant to change this situation, and to a certain extent it weakens the authority of team leaders or section chiefs.

Implementing APS is a complex and challenging task, requiring organizations to remain flexible and innovative when facing several key difficulties. Resolving issues such as data quality, technical infrastructure, organizational change, and cost management is crucial. Implementing APS is a complex and challenging task, requiring organizations to remain flexible and innovative when facing several key difficulties. Resolving issues such as data quality, technical infrastructure, organizational change, and cost management is crucial.
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