Past, present and future, to realize the aim of product CTQS (i.e., lower cost, faster time to market, higher quality and better service) with manufacturing intelligence, few manufacturers have no longer engaged in product related production decision support problem (P-DSP). However, P-DSP solving (P-DSPS) is a multi-criteria decision-making problem, which is context sensitive in solution objects-attributes and chaos in the decision process of manufacturing knowledge collaboration and reuse. To alleviate these limitations, this paper presents a novel triple deep workflow model for P-DSPS. Driven by a wicked task query, the proposed workflow of P-DSPS (WP-DSPS) has the function to retrieve similarity-based alternatives from domain knowledge driven solution flow (KSF) and to evaluate with expert knowledge collaboration from knowledge driven decision flow (KDF) based on utility theory under the task event driven control flow (ECF) strategy and operation logic. In the view of alternative adaption, a domain knowledge ontology-based degree of similarity (DoS) determines the P-DSPS alternatives width, a utility function-based degree of decision (DoD) determines alternatives quality, and a belief-based knowledge fusion technique is used to synthesize decision conflicts with a consensus degree (CD). To support the proposed models, a workflow-based system prototype is proposed and validated in two case studies.

过去、现在和未来，为了以制造智能实现产品 CTQS（即更低的成本、更快的上市时间、更高的质量和更好的服务）的目标，很少有制造商不再从事与产品相关的生产决策支持问题（P- DSP）。然而，P-DSP求解（P-DSPS）是一个多准则决策问题，在制造知识协作和重用的决策过程中对求解对象-属性和混沌具有上下文敏感性。为了减轻这些限制，本文提出了一种新的 P-DSPS 三重深度工作流模型。由邪恶的任务查询驱动，提出的 P-DSPS (WP-DSPS) 工作流具有从领域知识驱动解决方案流 (KSF) 中检索基于相似性的替代方案的功能，并基于效用理论从知识驱动决策流 (KDF) 中与专家知识协作进行评估任务事件驱动的控制流 (ECF) 策略和操作逻辑。在备选适应方面，基于领域知识本体的相似度（DoS）决定了P-DSPS备选方案的宽度，基于效用函数的决策度（DoD）决定了备选方案的质量，基于信念的知识融合技术用于合成具有共识度（CD）的决策冲突。为了支持所提出的模型，在两个案例研究中提出并验证了基于工作流的系统原型。