Challenges
During the first conversation with Translogix team they mentioned common issues which involved their dependency on manual process.
Workers manually recorded stock and processed orders which lead to common errors in inventory counts and order fulfilment.
High labor wage per hour and the overworking of labors were among the factors that they were concerned about. Due to the high peak times, a lot of labor was required which caused a strain in the budgets and paying for bulk wages.
The management system was not well integrated with its inventory tracking as there was no centralized system which shows the current inventory status in real time.
Their Current System did not provide real time inventory capabilities instead required a lot of manual efforts to be done during the checking or counting of the stock. This uncertainty or reach of data out of sync caused a lot of overstocks or stockouts, making the order fulfilment and scheduling difficult.
Improving ability to cope with seasonal demands was a problem for them as their manual system failed when requirements became much more than what they expected. This situation lead to delays in deliveries which frustrated customers and harmed TransLogix’s reputation.
Solutions
By considering challenges faced by Translogix, we designed a Dynamic Warehouse Management System (WMS) Prototype, utilising advance tools and technologies to streamline operations and improve workflow efficiency.
We integrated IoT sensors throughout the warehouse to enable continuous and automated tracking of inventory levels. These sensors provide instant updates on stock movement and eliminating manual counting errors which significantly reduced labor dependency.
Advanced AI algorithms were deployed to optimize picking and packing routes within the warehouse. This drastically reduced the labor hours required and minimized worker fatigue which improved productivity especially during peak times.
The prototype utilized AWS Cloud services which provide Translogix with a centralized, scalable and secure platform for data storage. Real-time inventory data was synchronized and made accessible across all management levels which resolves data fragmentation issues and eliminates overstocks or stockouts.
We utilized Python to seamlessly integrate IoT sensors, AI-driven algorithms and AWS cloud infrastructure into a cohesive system. This simplified method improved overall operational efficiency by ensuring seamless compatibility across many technologies.
We developed interactive and real-time analytics dashboards using Tableau. This analytics dashboard provides warehouse managers instant insights into inventory levels, order statuses and performance metrics. This enabled proactive decision-making and significantly improved Translogix’s ability to handle seasonal demands effectively.
