Case Study
[Translate to English:] ROI Case Studie - Smart Factory Planning

Smart Factory Planning

Smart planning for smart factories

What does the ideal factory of the future look like? Do products there control their manufacturing completely independently? Or is it more about the perfect choreography of people and machines? When planning a "Smart Factory", companies often lose themselves in different ideas about which technologies or organizational forms represent the best possible way into the future. A "big picture" of where the journey is to go and how the implementation can function in concrete terms is seldom available.

In this case, a company from the pharma & 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.


An automobile manufacturer extends the assembly line of a premium model by two model series within five months. The volume of finished cars is expected to increase by 85%, while product quality and lean management are expected to reach a higher level of performance.


ROI-EFESO approach

The project team develops a scalable approach for lean transformation of the plant. After starting in individual pilot areas of assembly, it transfers the improvements to the current line and finally, with further lessons learned, to the ramp-up of the two new models.


Lessons learned

Visualize lean theory and make it tangible; involve employees from all relevant areas at an early stage and quickly try out what they have learned in the line; ensure a solid methodical foundation, in this case 3P.


ROI-EFESO success model

Comprehensive lean transformation in three dimensions: in the technical (manufacturing) system, in the management structures and with regard to the lean skills or "mindsets" of the employees.


ROI-EFESO Scan determines Smart Factory potentials

The particular challenge in this project was that very different product groups and lines had to be integrated within a maximum period of four weeks each. Workflows and performance indicators varied by line and plant, with different digitization needs and priorities. Therefore, at the start of the project, it was important to get a clear picture of the status quo of the degree of maturity and the requirements per location. 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 in terms of time and content for the digitization of manufacturing sites. A project team consisting of employees of the locations 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: Enter status quo

At first, it was all about taking stock: what has already been digitized in the works? Which ongoing projects exist? Are there any special features and requirements that need to be considered? 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: Sketch Big Picture with directions of impact

On the basis of these findings, the project team held a joint workshop with the plant management to determine the main directions for each site. The focus was not only on topics that the management considered to be particularly exciting and interesting, but also on development scenarios and location strategies. The result was a big picture that ensured a common understanding among the workshop participants as to where the journey should take them. The commitment for the joint next steps was correspondingly high.

In the workshop, the participants also determined the different directions of digitization of the respective locations. These included topics such as data transport, smart analytics or digital twins for the manufacturing process, smart material flow and driverless transport systems (AGVs). Since the company produces a triple-digit million euro volume of several pharmaceutical products per year, it moves large quantities of material through various process steps - the necessary processes are correspondingly complex and costly. For example, the AGVs will help to make future material flows 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 directions. For example, it identified the areas with the highest potential for driverless transport systems, the size in which the company would have to invest and the economic benefits. From this, it was possible to derive very precise statements regarding profitability / pay back of individual business cases.

Fourth week: Classify results in portfolio

At the end of the project, the project team for each location arranged approx. 40 key topics and initiatives from the previous weeks into a portfolio with three structure criteria:

  1. How large is the existing efficiency lever and how high are the possible cost savings?
  2. How much does the whole thing cost in the end?
  3. How quickly can the topic be implemented?

>100 million product units per year can be choreographed better with driverless transport systems.

Pilot projects for industry 4.0

The team filtered, among other things, three topics that are quickly realizable, cost little to implement and at the same time bring great benefits. The other focal points from the portfolio were added to the "open items" list in order to implement them at a later date. After a portfolio evaluation of all decision-making instances in the company, the implementation of the following measures was started:

  • Driverless transport systems for smart material flow
  • Cobots (collaborative robotics) to support employees
  • Real-time tracking systems for more data transparency and a more precise knowledge of the current stocks

Feasibility studies ensure successful applications

The project team carried out a feasibility study for the Cobot deployment. Several hundred meter long systems or lines in the plants provide for long running distances in order to feed the systems or to remove empty blisters. Cobots can relieve the employees considerably. A corresponding test run with a Cobot in a pilot environment showed that all processes work for a smooth and above all safe process. Even if this part can be assigned to classical automation rather than digitalization, it contributes considerably to the Smart Factory transformation of the plant.

Real-time tracking systems improve information flow

In this case, even the company could not say 100% exactly where stocks are located in the plant before planning its Smart Factories. This lack of transparency is particularly annoying when machines are retooled and the required parts are missing. This has no effect on the quality of the end product, but often a considerable percentage of plant availability is Lost. In the worst case, parts that are needed to start manufacturing are not available or cannot be found, so that the production line is at a standstill.

Real-time tracking solutions with geofencing and RFID technology, which allow direct location of the plant components, were therefore shortlisted for top digitization projects. The company can thus track seamlessly where which article was stored and used and how, and trace at all times what is happening in the system. 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 locations. Already in the planning phase, it was able to improve the quality of the process with the help of the pilot projects and thus the operational excellence at the sites. And both these successes and the lessons learned from the described project phases will of course support a successful roll-out of the Smart Factory Initiative to other locations in the future.

The team identified 40 relevant starting points for digitisation in one month.

Making Lean Principle a tangible experience

What unnecessary distances do employees cover at their assembly stations? Where are tools and vehicle parts stored unfavourably? Using video analysis, the project team quickly and comprehensibly illustrated where there were opportunities to save time or where tools should be used to minimize quality losses. Video analysis also contributed to the successful launch of the new models, as it allowed 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, it showed the essential milestones and (interim) results for C-level management, and on the other hand it could be used to address, escalate and advance cross-departmental issues.

Encouraging the joy of experimentation

Many employees tried out the theory of lean principles and methods directly in their work area. This not only made what they had learned tangible, but also motivated them to search for further time savings. For example, when assembling seats in limousines, 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 car for tools and parts that follows the vehicle on the conveyor belt and can be quickly pushed into the interior. This not only saves the material within reach and time when moving in and out - it also significantly reduces the risk of damage to the vehicle during this work step.

Simulate Hot Spots in the 3P Workshop

In this case it was added that different vehicle models were introduced to the assembly line with a very tight schedule. Many processes then vary, such as the wiring, which is more extensive and complex in the new sedan than in the other two models. Since this was also the first series, there was no knowledge of the problem points. The project team therefore took a two-track approach: for the ongoing production of the limousine with the classic lean approach. For the new model, it identified the "hot spots" with the launch managers in advance: 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 lies in the improvement of internal and cross-company logistics, production optimization as well as the increase of efficiency and effectiveness in the product development process. In addition, Werner Bick supports companies in the digital transformation process from strategy to implementation of Industry 4.0 / IoT solutions.

Further information can be found here.

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