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Smart Factory Planning
Smart planning for smart factories
What will the ideal factory of the future look like? Will products control their production completely independently? Or is it more about the perfect choreography of people and machines? When planning a "smart factory," companies often get lost in different ideas about which technologies or organizational forms represent the best possible path to the future. A "big picture" of where the journey should go and how implementation can work in concrete terms is rarely available.
In this case, a company from the pharmaceutical & life sciences sector is developing four of its plants in Europe into "smart factories". Together with ROI-EFESO, it first created such an overall picture as a planning basis for the upcoming transformation processes at the sites - and then tested suitable technologies in pilot projects.
Challenge
In just four weeks, a pharmaceutical & life sciences company wants to plan key thrusts for the smart factory transformation of four plants.
MOREROI-EFESO approach
The project team is developing a "big picture" as a planning basis for the upcoming transformation processes and is testing three prioritized technologies in pilot projects.
MORELessons learned
Obtain commitment from all decision-making levels early; consider ideas from the line, but prioritize implementation based on need.
MOREROI-EFESO success model
Already in the planning phase, filter out a few core topics that can be realized quickly, cost little to implement, and at the same time bring a great benefit.
MOREROI-EFESO Scan determines Smart Factory potentials
The particular challenge in this project was that very different product groups and lines had to be integrated in a maximum period of four weeks each. The workflows and performance indicators varied from line to line and plant to plant, with correspondingly different needs and priorities for digitization. Consequently, at the start of the project, it was important to first obtain a clear picture of the status quo of the maturity level and the requirements for each site. This is exactly what ROI-EFESO determined with its Smart Factory Scan in just four weeks.
The scan is an assessment tool that collects and structures all factors relevant to the digitalization of production sites in terms of time and content. A project team consisting of employees from the sites and ROI-EFESO consultants staggered this in the following sections:
The ROI-EFESO Smart Factory Scan checked 4 plants in 4 weeks for optimal starting points for digitization.
First week: Capturing the status quo
At first, the focus was exclusively on taking stock: What has already been digitized in the plants? Which ongoing projects exist? Are there special features and special requirements that need to be taken into account? Good approaches were recorded in order to evaluate them later in the context of all measures and projects in the plants. A central component of this first step was also to collect the most important basic data in the sense of baselining.
Second week: sketching out the big picture with thrust directions
Based on these findings, the project team defined the main thrust areas per site in a joint workshop with the plant management. The focus was not only on topics that the management group considered particularly exciting and interesting, but also on development scenarios and site strategies. This resulted in a big picture that ensured a common understanding among the workshop participants of where the journey should lead. The commitment to the joint next steps was correspondingly high.
In the workshop, the participants also defined the different digitization thrusts of the respective sites. These included topics such as data transparency, smart analytics or digital twins for the manufacturing process, smart material flow and automated guided vehicles (AGVs). Since the company produces quantities of some pharmaceutical products in the triple-digit millions per year, it moves large quantities of material through various process steps - and the processes required for this are correspondingly complex and costly. AGVs, for example, are expected to help make the future flow of materials more cost-effective and transparent.
Third and fourth week: Deep dives clarify details
In this phase, the project team dealt with so-called "deep dives", i.e. the technological and economic details of the defined thrust directions. For example, it identified the most promising areas for driverless transport systems, the scale of the investments the company would have to make and the economic benefits. From this, very precise statements could be derived with regard to the profitability/payback of individual business cases.
Fourth week: Classifying results in a portfolio
Finally, the project team sorted around 40 key topics and initiatives from the previous weeks into a portfolio with three classification criteria for each location:
- How big is the existing efficiency lever and how high are the possible cost savings?
- What does the whole thing cost in the end?
- How quickly can the topic be implemented?
>100 million product units per year can be better choreographed with automated guided vehicles.
Pilot projects for Industry 4.0
Among other things, the team filtered out three topics that can be realized quickly, cost little to implement and at the same time bring a major benefit. The other focal points from the portfolio were placed on the "open items" list to be implemented at a later date. After a portfolio evaluation of all decision-making instances in the company, the implementation of, among others, started:
- Automated guided vehicles (AGVs) for a smart material flow
- Cobots (collaborative robotics) to support employees
- Real-time tracking systems for more data transparency and a more precise knowledge of the circulating stock.
Feasibility studies ensure application success
For the cobot deployment, the project team conducted a feasibility study. Several hundred meters of equipment or lines in the plants make for long walking distances to feed the equipment or remove empty blisters. Cobots can considerably reduce the workload of the employees. A corresponding test run with a cobot in a pilot environment showed that all processes function smoothly and, above all, safely. Even if this part is to be assigned to classic automation rather than digitalization, it contributes significantly to the Smart Factory transformation of the plant.
Real-time tracking systems improve information flow
In this case, the company was also unable to say exactly where which stocks were located in the plant with 100% accuracy before planning its smart factories. This lack of transparency is particularly annoying when machines are retooled and the required parts are missing. While this has no impact on the quality of the end product, a significant percentage of plant availability is often lost. In the worst case, parts needed to start production are not available or cannot be found, so the production line comes to a standstill.
Real-time tracking solutions with geofencing and RFID technology, which allow the direct location of plant parts, therefore made it onto the shortlist of top digitization projects. The company can thus seamlessly track where which item was stored and how it was used, and understand what is happening in the plant at any time. The information generated by the smart geofencing systems can also be used for classic ERP processes.
With these digitization initiatives, the company is optimally equipped for further smart factory transformation at all four sites. Already in the planning phase, it was able to improve the quality in the process and thus the operation excellence in the sites with the help of the pilot projects. And both these successes and the lessons learned from the project phases described above will naturally support a successful rollout of the Smart Factory initiative to other sites in the future.
The team identified 40 relevant starting points for digitization in one month.
Making the lean principle tangible
Which unnecessary distances do employees cover at their assembly stations? Where are tools and vehicle parts stored inconveniently? Using video analysis, the project team quickly and comprehensibly illustrated where there are opportunities for time savings or where tools should be used to minimize quality losses. Video analysis also contributed to the successful launch of the new models, as it enabled the employees to rehearse and refine new workflows. The visualization of the entire lean transformation in the plant with a project map, the "control room," also proved to be very helpful. On the one hand, this showed the key milestones and (interim) results for C-level management; on the other hand, it allowed cross-departmental issues to be addressed, escalated and driven forward.
Encouraging experimentation
Many employees tried out the theory of lean principles and methods directly in their own work areas. This not only made what they had learned tangible, but also motivated them to look for further time savings. One example: During seat assembly in the sedan, the employees distributed their tools and smaller components in the footwell and on the seats. During the ramp-up of the coupe, the team had already developed and tested an assembly trolley for tools and parts that follows the vehicle on the conveyor belt and can be quickly pushed into the interior. This not only keeps materials within easy reach and saves time when moving in and out - it also significantly reduces the risk of damage to the vehicle during this step of the process.
Simulating hot spots in the 3P workshop
In this case, the situation was compounded by the fact that different vehicle models were introduced into the assembly line with a very tight schedule. Many processes then vary, for example in the wiring, which is more extensive and complex in the new sedan than in the other two models. In addition, since this was the first model series, there was no knowledge of problem points. The project team therefore took a two-pronged approach: for the current production of the sedan, using the classic lean approach. For the new model, it identified the "hot spots" in advance with those responsible for the launch: What are the fundamental differences between the models? In which processes is there more content?
Your expert for Smart Factories
Prof. Dr. Werner Bick has been a general representative of ROI Management Consulting AG since 1999. His professional focus is on the improvement of intra- and inter-company logistics, production optimization as well as efficiency and effectiveness enhancement in the product development process. In addition, Werner Bick supports companies in the digital transformation process from strategy to the implementation of Industry 4.0 / IoT solutions.
Further information can be found here.
Contact: Phone: +49 89 1215 90-0 / E-Mail kontakt(at)roi.de