ipolog Drives Logistics Planning Innovation at BMW
Challenges of a constantly changing market
- Situation: Increase in individualized products,
- The challenge: Difficult communication due to complex products.
- The solution? Virtual layout planning in the digital twin
The increase of individualized products means that companies need to adapt and reschedule production faster than ever before. Collaboration across departments, regions and even countries can quickly lead to misunderstanding and misinformation, especially when working with large amounts of data. Existing systems and factories are often unable to cope with the increasing demands of the current market.
To overcome these challenges, BMW uses a digital twin and chooses ipolog software as an expert planning tool for operational use.
With the possibility of virtual layout planning and the Digital Twin for logistics planning, BMW is able to ensure holistic production logistics planning and to integrate information consistently and across departments in a holistic database. Working in virtual space enables optimal, cost-efficient intralogistics planning and effective collaboration.
BMW faced the following challenges
Integrating all databanks into one holistic system:
BMW was searching for a better way to save and share the vast quantities of planning data that was spread across planning departments and management. Despite already using intuitive tools and intelligent algorithms, BMW was still reliant on Excel spreadsheets for their logistics planning. The risk of misinterpreting or misplacing important information was high. According to Julian Winzer, who works on Project Innovation und Industry 4.0 at BMW, “We don’t believe that we will continue to rely on Excel lists more and more in logistics planning. We need a data set without Excel that marries the actual data with the plan data.”
Collaborating across teams and across borders:
With planning, production and management teams stationed around the world, BMW needed a data management system that could handle high volumes of data and spontaneous changes of plan. BMW was also looking for a way to easily and efficiently view and optimize planning results – and to do so together with colleagues from all over the world.
Integrate existing systems and factories into a digitalized future:
BMW already had many existing systems and production factories in place. Finding a cost-efficient way to update their logistics and assembly for a digitalized future would require a tool that could evaluate existing systems and then provide optimization suggestions within the sphere of realistic possibilities.
Goals for Improvement for BMW
By using ipolog as a digital planning and management tool the following goals could be achieved:
- Vast quantities of data from various programs, algorithms and locations could be integrated into one holistic databank.
- Planning and management teams from across the globe could easily collaborate in 2D, 3D or virtual reality from their current locations.
- Existing systems and factories could be updated and prepared for a digitalized future.
- Digital twins could be built and future planning activities could be carried out on this basis.
The solution steps of ipolog, the planning tool
Step 1
Initial layout preparation via layout data from CAD systems
Step 2
Preparation of a logistical quantity structure with all relevant information on parts supply
Step 3
Merging of layout and quantity structure in a scenario
Step 4
Integration of container data, shift plans, process times and staging requirements
Step 5
Set-up of supply and disposal processes for subsequent calculation of planned times and required resources
These great results were achieved
Database integration::
BMW’s virtual reality tool ‘Colab’ is connected to the ipolog software. This means that the planner can decide whether to work in 2D, 3D or virtual reality and all changes are synchronized within the database to create data consistency. It also makes it easier to compare planning scenarios.
According to Nadine Wollinsky, a consultant at ipolog, “Afterwards, calculations and evaluations can be run via ipolog to get quick results of scenarios. Using the KPI monitor, scenarios can be compared with each other at a glance based on individual key performance indicators. This provides massive support to the planner and management in decision making.”
“We started with a database and coupled it with ipolog – this is how we achieved the visualization of a smart database.”
Collaboration:
With the help of ipolog, BMW is now able to view, plan, and collaborate on planning scenarios in 2D and 3D, regardless of where employees are located.
BMW also uses the ipolog software for employee training. Employees are able to put on VR glasses to “touch” and move objects. This is an obvious advantage for BMW in terms of Industry 4.0..
“This simply means that we have created a visualization in which we can plan in 3D, but also enter the VR world in the same way. It’s not just about viewing, I can also operate containers or shelves. And the best thing is: Not only can I do it on my own, but I can also, for example, meet my colleagues from Mexico and Spartanburg virtually and optimize the whole thing at the same time. This means that employees can be where they want to be and they no longer have to fly to see a process. In this way, we can significantly increase sustainability. This is not science fiction, it’s already in real use at our company,”
Brownfield:
BMW can also use ipolog to optimize its current brownfields.
“We can see all this in 2D or 3D – how much space is left on the line and how containers and shelves can be better planned and utilized. We have also integrated automatic calculations into ipolog, primarily to calculate process times and therefore personnel requirements. We can also evaluate space utilization or determine resource requirements,” says Wollinsky.
“We can drive through the brownfields with 3D scans and see our containers, shelves and structures. Then we add labeling or object recognition to teach the software what the objects are. And then other containers can be identified using AI.”
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