Our recent post Getting Started with Industry 4.0 lays out a path to the future of smart and modern manufacturing. The best way to achieve your Industry 4.0 goals is to create a roadmap for converting, upgrading or adding new systems that are the backbone of this digital transformation. Unfortunately, many companies will try to find ways to use their existing technology to make this transformation. However, they might find limited success with simply attempting to add-on to their current systems. In many situations, current manufacturing and production management systems will have to be upgraded or replaced. Here are some ideas on how to start taking steps with some backbone technology which are a platform for Industry 4.0 growth, while keeping pace with the competition.
Where to Start
For most manufacturing companies, the biggest bang from the Industry 4.0 journey will come from improvements on the shop floor. Focus on factory floor information. This will include understanding the information source and distribution methods for:
- The communicating and coordinating of production activities. For example: schedules (to-do lists), job packets, labor logs, quality sample/test data recording.
- Tracking the time of the entire production process from “release” to finished goods “put-away”, as well as, the recording of operational detail information such as labor time, machine set/run time, down time, wait time and machine/equipment data capture.
- Distributing and controlling documentation kept in engineering and quality department’s systems and paper files used on the factory floor, such as, test sampling, drawings, parts programs, recipes, etc.
In some cases, the underlying technology isn’t up to the demands of modern manufacturing. For example, if your shop floor systems are simply focused on accounting information and not on the execution of factory floor activities, then production and process improvements will be hard to find and impossible to implement. Paperless factory floor “execution” systems have underlying tech to provide this level of data capture and control that provides manageable, stable and sustainable systems from both a scheduling and tracking standpoint.
Industry 4.0 requires a fairly deep understanding of the production process at each of the operational steps, as well as, in between each step (bottleneck and wait time) on the factory floor. Knowledge of these activities can provide insight into the potential use of autonomous vehicles to improve part flow through the factory and the use of robots, co-bots and/or historian/recipe management to improve the speed and quality at specific operations.
Better management at a granular level
Real-time visibility to the flow of activities from one operation to another (inter-operational) along with (intra-operational) data capture of production processes must be combined with the ability to make rapid, fact-based decisions.
In addition to real-time visibility, is the backend analytics of what happened in both the movement of work through the factory floor, as well as, the capture of operational (quality, testing, recipe, machine) process data. If there are delays or other production problems, capturing the “who, what, where and when” is paramount. This is a potential place to use AI for improved analytics. It is also a place to evaluate the use of Industry 4.0 sensors to help detect and correct problems quickly. You simply can’t achieve this level of visibility and process improvement opportunism with accounting oriented interfaces.
Beyond the factory floor
Another example that’s particularly critical to making moves in a positive Industry 4.0 direction is the implementation of the newest shop floor scheduling optimization technology. Scheduling solutions that will be able to leverage Industry 4.0 technology will requires finite and multi-constraint (people, tools, equipment) logic. They can present the schedule in an easy to understand Gantt format providing a “visible chain” from customer sales order (specific demand) linked all the way through the Bill-of-Material and to purchased items. It should schedule in increments measured in seconds and minutes, not days or even in shifts. It should provide true and accurate Capable-to-Promise (CTP) estimates for new customer orders. And these schedules must be enforced via dynamic dispatching on the floor so that compliance to the schedule can be obtained. If the factory floor activities cannot execute to this optimized sequence and compliance is not obtained, then find and use the newest analytical tools to understand why not.
Your next step
To take advantage of the efficiency of IoT, robotics, Big Data (Data Lakes) and AI, you need foundational systems, as mentioned above, that can support the rapid data input, large data volumes (example: tags on machines) and the pinpoint scheduling required to provide the real-time insight necessary for rapid decision support, as well as, tools to help identify areas of production and process improvements.
If you are trying to achieve Industry 4.0 by working with ERP scheduling or data collection and have paper based production systems, your efforts are doomed to failure. At the very least, they will be costly and cumbersome, without ever reaching increases in speed, accuracy, optimization and visibility.
That’s why it makes sense to start your journey to Industry 4.0 by implementing or upgrading to a state-of-the-art MES and APS. An MES has been built from the ground up to receive input from a variety to sources, ERP, APS, Labor, Machines, Documents, Quality, Test Equipment, Tags and Sensors. APS provides rapid shop floor scheduling with optimization software to help ensure efficient operations and minimal downtime. These systems can react quickly to process anomalies such as downtime, scrap or rework, and provide quick insight into current conditions, so your team can make fact-based decisions in the best interests of the company and your customers. These systems are truly the heart of Industry 4.0, and it should be the first step in the journey for every manufacturing company.