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Compliance systems for dangerous goods sea transport

Hazcheck Detect

A cargo screening tool that detects misdeclared or undeclared dangerous goods in containerised shipments. Non-compliant cargo can be detected within seconds. Last minute changes to bookings are picked up in real time so problematic cargo is not loaded onto the ship.

Product Overview

Hazcheck Detect is an API based, integrated, cargo screening solution that detects misdeclared and undeclared dangerous goods in containerised shipments. Hazcheck Detect uses constantly evolving libraries of rules. It can accept full customer booking data, and screens whenever changes are made within clients own systems (generating a new API each time), with the aim of identifying suspicious cargo to users for thorough investigation.

Undeclared DG – identifies cargo that is not declared as DG; suspicious items are identified that should be declared as DG.

Misdeclared DG – checks focus on cargo which is declared as DG, but may not be declared as the correct DG.

The use of realtime cargo screening allows non-compliant cargo to be presented to users within seconds, not hours, or even days which are more typically associated with manual or batch process systems. Last minute changes to bookings, declarations, Bills of Lading and shipping instructions can be picked up as they occur. This means that intervention can take place much earlier, cargo descriptions can be investigated before containers are loaded or arrive on port. This immediate response prevents such cargo from being loaded onto a ship avoiding the risk of life threatening incidents such as ship fires.

Responses are presented to users either by return API messages or via the Hazcheck Detect user interface (UI) Case Management functionality. Here users may review and process suspicious cases. The UI is highly configurable allowing priority cases to be assessed quickly and efficiently with semi-automated workflows.

As more customers adopt Hazcheck Detect, libraries of rules are being refined to reflect a more consistent approach throughout the industry to cargo screening. The same rules and policies may be applied across the major shipping alliances operating globally.

As endorsed by the World Shipping Council.

Click on our 1 minute Hazcheck Detect overview video below

Also, see the Q&A discussion YouTube video below with James Douglas, Exis CEO and industry publication HCB for more information.

Features

Almost Real-time and Continuous Screening – Screen the same data set at any stage of the booking process and receive almost instant feedback

Complex Queries – Most queries are viable using the query syntax, but some may have additional complexity, or may require the ability to lookup external data, such as DG info, substance indexes, etc.

Rules Libraries – Industry groups can agree to share standard libraries with common terms.

 

Benefits
  • Complex and distinct libraries can identify both misdeclared and undeclared cargo items
  • Libraries of rules can be shared and are constantly adapting to help to identify new and evolving risks.
  • Data always updated with current regulations
Examples of common misdeclared dangerous goods

According to the U.S. Department of Transportation, commonly shipped undeclared hazardous materials include, but are not limited to:

  • Agricultural: ammonium nitrate fertilizers, pesticides
  • Air conditioning: Refrigerant gases
  • Automotive: Lead-acid batteries, air bag inflators, seatbelt pretensioners, fuel injector cleaners, gasoline, diesel fuel
  • Camping and outdoors equipment: fuel gels, propane “tanks”, matches, flares, scuba “tanks”
  • Construction: adhesives, sealants, tars
  • Fire-fighting equipment: fire extinguishers
  • Household goods: aerosol spray cans, perfumes, fireworks, oil-based paint related materials, adhesives, lighters, drain cleaners, pepper sprays
  • Medical: Oxygen “tanks”
  • Motorized vehicles, tools, and equipment: cars, boats, generators, engines, lawnmowers
  • Pool maintenance: chlorinating tablets or granules
Hazcheck IMDG Code eLearning

Case Studies

Related Case Studies

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