Warehouse Automation in the Automotive Industry

 

Background and Challenges

An automotive company had the golden opportunity to start from scratch in a new warehouse after an acquisition. They decided to take this opportunity to not only leave behind the challenges of their current operations, but to plan for the future and automate where possible. Forecasts for the coming years were looking good and would most likely put the current operations under pressure, since most of the processes were very manual and labor intensive. Some of the key operational challenges were:

  • Traffic and Congestion: There was no clear distinction in terms of flows, meaning that forklift traffic, human traffic and picking and transportation flows would randomly intersect- leading to unsafe situations and inefficiencies resulting from congestion.

  • Poor Inventory Visibility: Scannable inventory locations did not exist, and locations were not systematically supported. Products would have a main, preferred location- but would also be stored in additional overhead/back-up locations. Because of this, operators would find themselves looking for product in the warehouse.

  • Transportation: An internal train system served as the interface between the production and the warehouse. Different Finished Goods and Raw Materials- trains would drive around, following their assigned routes and pick up/drop off goods. Because of unbalanced routing and the size of these trains, one could often find them waiting for an aisle to free up.

  • Picking: Kanban Cards would get picked up from the production line on a frequent basis, serving as a basis to signal the need for product. This product would then be picked in the warehouse, ideally from its primary location. Since replenishment was not consistently performed, products would end up being out-of-stock and FIFO principles could not always be respected.

  • Outbound Shipments:  The creation of outbound shipments was considered very labor intensive and also came with ergonomic challenges. While building the requested pallets for the customer, respecting customer requirements re: labeling, palletizing and order quantities, operators would find themselves waiting for and looking for (the right) product or building pallets based on tribal knowledge.

  • Contamination: Because of the different transportation flows, cardboard and waste would be driven around the warehouse. All Raw Material and Finished Goods would also pass by the waste area of the warehouse, potentially leading to contamination- which could pose considerable risks to the production quality.

The existing warehouse operation was very manual and could pose risks to productivity if replicated in the new larger facility with increased demand. Establish’s goal was to determine how these processes can be improved while also creating a warehouse design that enables the growth.

The Evaluation and Analysis

Establish evaluated the storage and fulfillment processes in order to identify the gaps and challenges in the operation. In parallel, warehouse data was gathered, analyzed, and profiled to understand the operational volumes and identify opportunities for improvements. After the analysis, the following observations were determined:

  • Up to 80% of the train drivers’ time can be considered non-value-added.

  • On the Raw Material Side, only 34 items need (more than) a full pallet space, while 189 items should not need more than a half pallet position.

  • On the Finished Goods side, 21% of the products get ordered as quantity of 1 box, while 70% of the orders consist of less than 10 boxes.

  • Forecast shows growth at a 39% rate over the next two years.

The Recommendations

Because of time and resource considerations a prioritization was made, resulting in different Phases of Improvement and Automation. Phase 1 focusses on getting the new warehouse operational and efficient, mostly by optimizing traffic and flows. Phase 2 leaves the opportunity for further automation through ASRS and palletizer, while Phase 3 can be seen as the start of a Continuous Improvement journey, including a potential Warehouse Management System.

Phase 1

a. Update the Picking Methodology, by using Order Pickers

First, a separation of picking and transportation activities was proposed, to avoid unnecessary traffic through the aisles and reduce the non-value-added time. Additionally, the proposed use of Order Pickers – allowing to pick at a box level at any level in the warehouse should allow for increased picking efficiencies and should alleviate FIFO and replenishment challenges. Moreover, order Pickers will pick onto racks (one per production line) to group items and deliveries. These racks will then be left in a drop-off/pick-up zone.

b. Design a Layout with Optimal Flow, leveraging Autonomous Mobile Robots (AMRs)  

The warehouse was designed to accommodate pallet racking, repacking/shipping stations, and inbound and outbound processing areas near the docks. Because of the separation of picking and transportation to production, less intersections, traffic and congestion is to be expected. The biggest efficiency gains come from implementation of Autonomous Mobile Robots (AMRs). These robots will be in charge of transportation from and to the warehouse, transporting around racks with Raw Materials and Finished Goods, constantly optimizing routing and transportation efficiency.

c. Safety & Contamination, dedicated traffic flows and intersection managers.

By assigning specific loops to dedicated means of transportation, the number of intersections was reduced and unsafe and inefficient scenarios were avoided as much as possible. For the little number of intersections left, intersection management technology should allow to manage those in an efficient and safe way. The AMR robots will also take into account additional safety and speed requirements in zones where human and/or forklift traffic can be expected. 

Phase 2

a. Business Case for ASRS

Once operations in the warehouse are up-and-running, a next degree of automation should be considered. Given the fact that both on the inbound as on the outbound side, many items come in and go out of the warehouse on a box-level, the idea of box storage within an ASRS (Automatic Storage and Retrieval System) can take efficiency to a next level. This would also solve the issue of product visibility and availability without having a WMS, since the system will always know where each and every box is stored. While this degree of automation can further reduce manual work and will increase efficiency, it also comes at a cost- both in terms of implementation risk and cost, since it also has to integrate smoothly with the rest of the operations.

b. Business Case for Automated Palletizer

The pallet building of outbound shipments can be considered one of the most labor intense, ergonomically challenging and time-consuming activities in the warehouse. As a nice add-on to the ASRS storage solution, an integrated palletizer could further optimize this part of the value chain. A robotic arm can easily, efficiently and ergonomically build the pallets, taking into account customer requirements.

c. System Limitations and Further Room for Improvement

It was determined their current system did not support scannable inventory locations or other system functionalities that could alleviate some of the key challenge areas highlighted above, therefore, the non-fast-moving inventory was still slotted in alphabetical order in the short-term. Exploring a new WMS was a long-term recommendation. It was important to complete the move and allow the operation to settle before any drastic system changes. Implementing a new WMS would allow for flexible storage, logical slotting, improved inventory visibility, and other inventory management capabilities that were nonexistent in their current system.

The Results

All storage and operational requirements could be met in Phase 1 while providing easy scaling of the operation or transition to an automated solution in Phase 2. Non-value-added time could be reduced by 60% due to the separation of picking and transport and updated material handling equipment for picking. Further automation, such as AMRs, would further reduce idle time, manual labor and picking mistakes.