以热流率作为补偿的智能PID控制

本文以电加热流动热力系统为例，提出了一种以静态模型为基础．以热流率作为补偿的智能ＰＩＤ控制处理动态模型的方法．较好地解决了由于热流率的变化而引起的温度波动，在应用中得到了满意的结果．     

《机械制造技术》课程及主要实践环节的教学改革

结合多年的教学改革经历，论述《机械制造技术》课程教学改革的基本思路及其主要措施。以三个教改阶段中不同的培养目标与教改方案为例，论述各阶段的课程体系和教学内容，特别强调了教改必须与时俱进，必须突出各个时期的应用型人才培养特色。专业课的内容应该精简并有机地整合，内容应符合制造业发展的现状与水平，突出先进的及代表主流的制造技术，反映新技术与发展方向。同时探讨与该课程密切相关的生产实习、毕业设计等主要实践环节的教改措施，强调从工程实际要求出发培养学生的工程应用能力。     

Patterns of Advanced Manufacturing Technology Utilization and Manufacturing Capabilities

The objectives of this research are first to empirically replicate Advanced Manufacturing Technology (AMT) utilization taxonomies identified in foregoing research, second to investigate the relationship between patterns of AMT utilization and manufacturing capabilities attainment, and third to explore differences in context, and performance across AMT groups. Theories of performance frontiers and capability progression provide the basis for our hypotheses. Data were collected from 224 U.S. manufacturing plants in industries considered to have potential utilizations of AMTs. A cluster analysis of the data yields a solution that closely resembles a previous AMT utilization taxonomy, including four groups labeled, respectively, as Traditionalists, Generalists, High Investors, and Designers. Significant manufacturing capability differences across these four groups indicate that plants that utilize a broader scope of AMTs enjoy a greater breadth of manufacturing capabilities. The implied capability attainment pattern is consistent with cumulative capability theory. However, the results suggest that cost capability is not included in the capability mix when broad‐based AMT utilization is the enabler of capability gains. A post hoc exploration of the AMT groups indicates significant differences in performance across the groups. Collectively, the results extend prior research by providing added insights into the possible rationale and impact of AMT utilization patterns.     

高技术复杂度中间品进口会加剧制造业中间品进口依赖吗?

本文在测度制造业和服务业中间品进口技术复杂度的基础上,剖析了中间品进口技术复杂度对中间品进口依赖的作用机制及其作用渠道,并进一步分析了中间品进口技术复杂度对经济量增和质增的作用机制。得到的结论主要有:一是高技术复杂度中间品进口会加剧一国的中间品进口依赖,该结论在多维度检验中均稳健成立,这一机制不仅有助于高技术中间品先发企业成为制衡全球价值链的链主,还容易导致高技术复杂度中间品后发企业成为全球价值链的被俘获者和尾随者;二是高技术复杂度中间品进口通过抑制制造业的资本积累和科研人员规模扩大来加剧高技术复杂度中间品进口国的中间品进口依赖,中国的制造业和服务业中间品进口技术复杂度远高于自身经济发展水平,这使得中国承受的中间品进口依赖压力可能远高于其他国家;三是高技术复杂度中间品进口是经济量增和质增的重要推动力量,促进经济量增和质增战略与降低中间品进口依赖战略之间存在潜在冲突,这一潜在冲突也证实了中国当前以国内大循环为主体发展战略的科学性和正确性。     

High value manufacturing: Capability,appropriation, and governance

Manufacturing competitiveness is on many policy agendas, born out of a concern for firms in high-cost economies finding themselves outcompeted by low-cost rivals. Government policy makers and manufacturing firm strategists have put their faith in what we label as high value manufacturing (HVM). We see HVM as an incipient phenomenon currently in a situation of prescience, as something that is still “in-the-making,” with manufacturing firms trying to find ways to be able to step away from having to compete on price. This paper consults relevant strategy theories with the purpose to pinpoint the issues and problems that need to be accommodated for bringing HVM into being and for creating the effects that are anticipated. We found that HVM must be seen as a distributed activity, thus realizing complex functionality for a system-of-use, while being subjected to path constitution. For HVM to function, the firms involved need to find solutions to the capability problem, the appropriation problem, and the governance problem. We suggest that further research needs to involve itself in problem-solving activity to assist in bringing HVM about while simultaneously further developing strategy theory geared toward firms that are involved in a distributed activity like HVM.     

Stimulating effects of intelligent policy on the performance of listed manufacturing companies in China

Based on the pilot projects of intelligent manufacturing of the Ministry of Industry and Information Technology of the People’s Republic of China and the annual data reported by listed companies, this paper studies the effect of China's intelligent policy on the performance of listed manufacturing companies by using the panel data of relevant enterprises from 2011 to 2017, as well as the mechanism of impact. Our empirical tests, using the difference-in-difference method, shows that intelligent policy can significantly improve the economic performance of manufacturing enterprises by guiding enterprises to optimize their intelligent management, strengthening investment in intelligent equipment and promoting collaborative manufacturing. Further empirical tests show that the impact of intelligent policy on economic performance is different in time. In the later selected pilot enterprises, the impact of intelligent policy on their economic performance is more significant; there is regional heterogeneity in the effects of intelligent policy: in regions with low intelligence, the positive impact of intelligent policy on the economic performance of manufacturing industry is more significant. Based on these conclusions, relevant intelligent policy suggestions are put forward.     

Evaluation of Embedded Intelligent Real‐time Systems*

Over the past two decades, questions have surfaced about the effectiveness and contribution of intelligent systems to decision makers in a variety of settings. This paper focuses on the evaluation challenges associated with intelligent real‐time software systems that are embedded in larger host systems. With the proliferation of such systems in operational settings such as aerospace, medical, manufacturing, and transportation systems, increased attention to evaluations of such systems, and to resulting software safety, is warranted. This paper describes one such evaluation and proposes a set of evaluation criteria for embedded intelligent real‐time systems (EIRTS). Implications of the evaluation and the evaluation criteria are discussed.     

广东省与江西省制造业集聚发展状况的对比研究

对广东省与江西省两个差异显著的省区制造业集聚状况从不同角度进行对比分析:从区域方面对比分析,发现制造业在江西省比广东省在空间上更为集聚;从行业方面分析,发现两省最为集聚的产业基本上是一些资本或技术密集型行业,最为分散的产业是技术含量低的劳动密集型行业。一些资源加工型行业、资本技术密集型行业以及历史悠久的传统行业在广东省与江西省集聚态势差异显著。实证分析表明,影响两省制造业集聚的因素存在一定的差异,但也存在着相似性。导致差异的原因源于制造业在不同省区的自然优势、集聚效应以及内涵的差异,但政策与制度因素仍然是主导。     

Replanning the Master Production Schedule for a Capacity-Constrained Job Shop

This research examines the use of both frozen and replanning intervals for planning the master production schedule (MPS) for a capacity-constrained job shop. The results show that forecast error, demand lumpiness, setup time, planned lead time, and order size have a greater impact on the mean total backlog, total inventory, and number of setups than the frozen and replanning intervals. The study also shows that a repetitive lot dispatching rule reduces the importance of lot sizing, and a combination of repetitive lot dispatching rule and single-period order size consistently produces the lowest mean total backlog and total inventory. The results also indicate that rescheduling the open orders every period produces a lower mean total backlog and total inventory when the forecast errors are large relative to the order sizes. This result suggests that the due date of an open order should be updated only when a significant portion of the order is actually needed on the new due date.     

Learning by Objectives for Adaptive Shop-Floor Scheduling*

Effective production scheduling requires consideration of the dynamics and unpredictability of the manufacturing environment. An automated learning scheme, utilizing genetic search, is proposed for adaptive control in typical decentralized factory-floor decision making. A high-level knowledge representation for modeling production environments is developed, with facilities for genetic learning within this scheme. A multiagent framework is used, with individual agents being responsible for the dispatch decision making at different workstations. Learning is with respect to stated objectives, and given the diversity of scheduling goals, the efficacy of the designed learning scheme is judged through its response under different objectives. The behavior of the genetic learning scheme is analyzed and simulation studies help compare how learning under different objectives impacts certain aggregate measures of system performance.