在多事的2020年之后, smart manufacturing technology remains at the forefront of manufacturing industry trends 2021年 as facilities continue to explore innovative ways to improve processes and efficiencies. 在2020年的动荡和复苏之后, 2021 brings a host of new smart manufacturing trends and technology applications that you will want to understand.
在这里, we will examine those trends and how they can help optimize your operations and contribute to the health and 弹性 of your business.
Smart factory trends 2021年 are focused on recovery and preparedness, 可以肯定的是, but they are also building on developments and advances in technology that have long been in the works — independent of the COVID pandemic and response. 这些趋势包括:
- 更多的远程和非现场操作工作机会: Safety, 灵活性, convenience — the reasons for this trend are numerous and ever-increasing. 尽管世界在新冠肺炎的阴影下恢复了正常, facilities are retaining remote work options and continuing to investigate ways to build even greater 远程访问 into their operations.
From sensor monitoring to virtual maintenance and troubleshooting via 工业物联网 数字孪生技术, the industrial world has proven that effective operations are possible even when personnel are not in person at the facility. This trend will only continue to grow as communication technology improves.
- An increased focus on the partnership between manufacturer and customer: Trust and confidence are two major themes of manufacturing in 2021, as the uncertainty of 2020 created a need for communication and relationship-building beyond merely transactional, 商品化商业——不管产品是什么. Manufacturers are increasingly expected to act as a true service-providing partner, 不仅仅是一种生产手段.
- 使用传感器监测机器健康和状态: 传感器技术 制造业多年来一直在崛起吗. 2021年将迎来关键的大规模突破, with sensors achieving more widespread adoption at an ever-more accessible price point.
The ROI for sensors will become more pronounced as more facilities use them to enable constant, real-time machine health and condition monitoring — yielding more effective maintenance, 更长的设备寿命和更高质量的输出.
- Safeguarding profit margins through increased proactivity and efficiency: 传感器还能实现预测性维护等战术, where machine performance data is analyzed to detect minor fluctuations in areas such as vibration, which can indicate the beginnings of more significant problems down the line — allowing the facility to address these problems at a convenient time. 这种主动方法减少或消除计划外停机时间, allowing facilities to reap maximum productivity through equipment operation.
- 一种更具有预测性的方法——超越维护功能: 鉴于一场全球性的灾难, a predictive approach to operations will be widely sought after at the macro level. Manufacturing businesses are understandably keen to get ahead of the next global disruption, 无论何时何地. 人工智能等技术 and big data mining will be increasingly drawn upon to run global scenarios that may help predict and prepare for these events.
- 人工智能的探索和采用: 人工智能也准备在生产车间取得突破, 准备好实现多年来增量采用的承诺, 以及机器学习等相关技术. 在追逐利润的竞赛中, AI technology can be used for more accurate forecasting and planning of maintenance, 生产能力, 库存, 销售, 和更多的.
- 人事职能的改变-和学习机会: The growth in AI technology will require capable people to implement, manage and make sense of it — a far cry from the fear that AI will replace humans. The impending AI boom represents a great opportunity for manufacturing employees to learn and advance their careers.
Manufacturing personnel operations may also change as organizations increasingly turn to resources such as 技术人力资源合作伙伴 使这些职能的价值和效力最大化.
- 合作机器人正在崛起: 类似的, human workers remain a critical part of hands-on manufacturing tasks themselves, although the technology to make those tasks easier is increasingly prevalent. Cobots (collaborative robots) are one such example — automation machines with smart technology and safety features that enable them to work nearly side by side with human workers.
- 技术驱动的供应链透明度和问责制: 智能技术将影响 供应链 也, 对于可靠性的兴趣, transparency and 灵活性 is at an all-time high following 2020’s disruptions.
人工智能等技术, vendor management software and blockchain will all play a role in the face of the 供应链 — no longer an intractable monolithic function, 但要有更多的责任和选择的自由.
- 场景规划的新思路: With smart technology such as AI and big data providing more insight into potential future disruptions to manufacturing, it is still incumbent upon managers and personnel to plan responses to these scenarios.
Typically, these scenarios would be limited to short-term disaster response, etc.; however, COVID has shown that more long-term problems must also be addressed. 因此, these planning exercises will go beyond immediate response planning to factor in agility, 灵活性, 弹性, 员工关系及长期恢复.
Of course, no one can reliably predict the future, as 2020 made abundantly clear. Though by looking at short-term 也 as long-term trends and focusing on big-picture themes (such as 灵活性, 可靠性, 远程访问, 维护合作伙伴关系, equipment monitoring and data-driven functions) manufacturing businesses can use these trend forecasts to remain well-positioned and advantageous in the competitive landscape.