Image
Overview
As EVs penetrate global markets, battery manufacturers are under tremendous pressure to accelerate, improve accuracy and drastically increase warehouse responsiveness to production demands. In this environment, even small failures in inventory visibility or delays in moving material can quickly impact assembly schedules and downstream fulfillment.
Our client, the EV battery division of a global automotive and engine manufacturer, faced several operational constraints. Inventory visibility was limited, putaway and picking still relied heavily on manual judgment, automation workflows were not fully integrated, and warehouse operations were under increasing strain as demand volumes rose.
To surmount these challenges, the client sought Birlasoft’s expertise to modernize warehouse execution on Oracle WMS Cloud. Birlasoft deployed a standardized solution integrated with material handling equipment (MHE), middleware orchestration and PLC-driven automation, which resulted in significantly higher throughput, near 99% inventory accuracy and improved picking productivity. Below are the details of this engagement.
The Challenge
#1. Lack of visibility of real-time inventory
The client had the challenge of missing inventory information in storage and picking locations. Also, the system updates were not always up to date with the latest stock movement.
This translated into low confidence in stock decisions. This resulted in extra reconciliation work, inventory discrepancies and delays in sourcing key battery components during fulfillment.
#2. Deciding putaway and picking manually
Key decisions made in the warehouse, such as putaway and order picking, were based on operator experience and not system logic. This resulted in inconsistent storage patterns, longer travel distances, and unwarranted inefficiencies in both labor and space.
#3. Unstructured picking processes
Picking operations were ad hoc, first-in, first-served, with little prioritization or wave-based planning. This caused uneven load sharing, congestion at the floor during peak cycles, and lower total throughput.
#4. Automation workflows are not connected
Current conveyor and robotic systems were not deeply integrated into the warehouse management layer. So supervisors had to step in regularly to coordinate material movement and trigger actions on the warehouse floor. These manual hand-offs slowed operations and reduced the value of the automation already performed for the business.
#5. Difficulty in scaling up to meet growing EV demand
The rising demand for EV batteries was surfacing new limitations in warehouse processes. Manual, labor-intensive practices meant the operating model lacked the agility needed to respond to volume spikes or future growth.
The Solution
To address the challenges of warehouse execution and scalability, the customer partnered with Birlasoft to upgrade its operating environment using Oracle WMS Cloud. With its deep expertise in WMS-led warehouse transformation and MHE integration programs, Birlasoft developed a structured, automation-ready solution that improved execution efficiency, reduced manual dependencies, and created a scalable platform for future growth.
#1. Smart inventory placement & system-directed putaway
Birlasoft used slotting logic to make system-driven putaway decisions rather than operator discretion when configuring Oracle WMS Cloud. The storage recommendations were generated using zone rules, available space, product movement velocity, and handling constraints. This helped bring some consistency to where we put inventory and reduced travel time across the warehouse floor..
#2. Wave planning and picking orchestration based on rules
The warehouse previously had ad hoc picking processes. Next, to implement standardization, Birlasoft enabled rules-based wave creation based on shipping priorities, cut-off timelines, labor capacity, and pick zones.
The wave-planning logic was developed based on Birlasoft’s experience in high-volume warehouse environments. The first task for our team was to de-congest the floor and to better balance the workload throughout the operation. This will help sustain throughput during peak demand.
#3. Full integration with MHE and PLC systems
A critical part of the engagement was connecting Oracle WMS Cloud to the warehouse's conveyor, robotics, and AS/RS infrastructure. For this purpose, proven integration patterns, well-defined message contracts, and equipment ID mapping frameworks were used.
As a result, warehouse tasks were consistently translated into machine-level commands, and execution feedback was fed back to the system to maintain consistent control.
#4. Operational feedback and visibility into exceptions
The solution has been built as a closed-loop workflow orchestration platform with continuous feedback loops from task completions, jams, faults, and movement confirmations back into the WMS layer.
This was a key to improving inventory accuracy and providing operations teams with near-real-time visibility into task status and exceptions.
#5. A scalable, automation-ready warehouse base
Security data moved in waves, each followed by mock release testing against audit reports. Two security workbench tables captured late-cycle changes until go-live in a scheduled weekend window with hyper-care support.
Birlasoft designed a warehouse execution framework that would scale with future EV battery demand, using proven orchestration logic, queue management controls, and resilient middleware design.
Now the client can handle volume spikes and add more automation logic without interruption to operational continuity.
Results Delivered
With the new solution in place, the client is now experiencing greater execution efficiency and improved inventory management. At the same time, we also created a digital foundation that supports long-term growth goals alongside current improvements:
#1. Accelerated order execution and increased throughput
System-driven task orchestration and MHE integration to optimize material flow and accelerate the order-to-ship cycle time.
#2. ~99% Inventory accuracy
Real-time acknowledgment of task status and closed-loop updates helped us improve stock visibility and inventory accuracy.
#3. Enhanced Picking Productivity
System-directed picking and rule-based wave planning reduced the travel time and raised the number of picks per labor hour.
#4. Removal of manual dependency
Integrated workflows between the WMS, middleware and automation systems reduced the need for supervisory intervention and increased efficiency on the warehouse floor.
Do you want to modernize your warehouse operations? Transform the backbone with a WMS redeployment and achieve unmatched supply chain outcomes – call our experts to get started today.
