Supply chain damage caused major operation waste and scheduling issues. See how they fixed it.
Summary: An offshore drilling company was moving equipment from their operations base to a loading dock in South America before shipping it to an offshore drilling platform. Supply chain damage caused major operation waste and scheduling issues.
Product Solution: SpotBot Cellular
Offshore Drilling Case Study: SpotBot Cellular
Industry: Offshore drilling and exploration
Application: Offshore drilling equipment
Situation: A major offshore drilling company was moving equipment from their operations base to a loading dock 115 miles/185 kilometers away, on a coast in South America. From there it was loaded onto a ship and transported to a drilling platform 120 miles/193 kilometers offshore. The equipment consisted of various motors, pumps, and other gas injection equipment used for offshore oil and gas exploration. The motors and pumps were built into long metal cylinders. At the base of operation, nine cylinders are packaged within a thick steel container and loaded onto the back of a truck before taking a trip to the shipping yard. Once there, the container will sit two or three days before being placed on a ship for the final leg of the trip. A single rotation in this cycle will take five to seven days. At any given time, there are 80 containers of equipment either being transported from the base of operation, sitting at the shipping yard, or on a ship bound towards an offshore drilling platform.
Problem: The company’s equipment was frequently damaged during the trip which caused several problems
- Cost of the damaged equipment
- Operational downtime at the drilling site
- Interruption to a complex schedule
but there was no way to allocate blame. Without a checkpoint at the shipping yard, the damage wasn’t realized until it was already at the drilling platform. Workers claim there was not damage to the equipment when it left the operations base and the contractors at the shipping yard were not accepting fault. The company estimated that when equipment arrived damaged to a platform, they were losing $140,000 per day until new equipment arrived.
SpotBot Cellular gave the company the ability to:
- See where the damaging impacts were occurring.
- Identify the events that damaged their equipment.
- Identify a specific G-force level, direction, and acceleration of impact that would damage their equipment.
- Prevent damaged equipment from moving further through the supply chain, causing more delays and associated costs.
- Consider new container designs, equipment material, etc.
SpotBot Cellular Overview
Best in Class Impact Data
SpotBot Cellular generates accurate data on impacts up to 65G providing more than four times (4X) the range of the best competitive alternative (which captures impacts up to 16G). This range of impact monitoring is best suited for products between 100-60,000 lbs.
Longest Battery Life
With off-the-shelf lithium batteries, SpotBot Cellular delivers up to 80 days of monitoring (set to hourly summary reporting). This represents a battery life that is greater than 50% (1.5X) more than the next best competitor.
Flexible Settings & Download Capabilities
The user easily defines impact settings specific to the product being monitored and SpotBot Cellular will deliver a location and time stamp of alerts from impacts over the threshold. After the trip, the user can easily download a PDF file with the top ten largest impacts, a CSV file with the top 50 largest impacts, and a slot-time report from the SpotBot Cellular.
The SpotSee Cloud is where trip data is aggregated in real-time. Graphs are easy to read and include data such as specifics of impact with locations, impacts over time, impact histogram, and temperature.
SpotSee Cloud Features
- Access to your data from anywhere with a secure web portal
- Real-time reporting and tracking of incidents
- Alarms with location, time, impact g-level, direction of impact, and temperature
- Impacts-over-time visualization of each asset
- Histogram of the total impacts to an asset
- Temperature over time graph
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