Mkwawa Transforms Maintenance with Predictive Asset Management

Find out how MAS enabled predictive maintenance, cutting conveyor downtime by over 50% while improving reliability and data-driven decision-making.

Mkwawa transitions to condition-based, predictive maintenance with Maximo

Relaunching their plant in Morogoro provided an opportunity to modernize and optimize.

The Challenge

Mkwawa Leaf Tobacco Limited specializes in cultivation, processing, and supply of high-quality leaf tobacco to clients worldwide and supports thousands of tobacco growers.

When their core plant in Morogoro, located about 196 kilometres (122 miles) west of Dar es Salaam in the eastern part of Tanzania,
re-opened after being mothballed for nearly three years, the refurbishment and re-launch of operations marked a substantial investment. Mkwawa needed to ensure the investment delivered maximum value for years to come.

Robust data was also crucial to meet Mkwawa’s quality assurance and sustainability goals. To demonstrate environmental impact, they needed to easily monitor and mitigate key aspects of their production processes, including energy efficiency, waste management, and greenhouse gas emissions. However, Mkwawa couldn’t effectively collect asset data in their asset register, which made it impossible to retrieve information for traceability and reporting and lead to inefficient asset maintenance.

Our Solution

MDU set out to unify policies and procedures, consolidate data, and streamline workflows. The initiative included IBM Maximo as a centralized EAM system connected to 10 applications with over 70 integration points.

They turned to the Cohesive team of Maximo as a brainstorming partner in the ‘art of the possible.’ Together, they integrated the siloed systems and devised innovative solutions that leverage Maximo in new ways.

The Results

Mkwawa Leaf Tobacco Limited has transitioned from reactive to predictive maintenance, minimizing unplanned downtimes and maximizing productivity.

Following the implementation, conveyor belt downtimes at the plant dropped from 1,898 minutes (31.63 hrs) to 857 minutes (14.28 hrs) per year. A single repository for standardized asset information enables better decision-making and improved asset performance.

Scheduling tools, real-time reporting on KPIs and optimized labor management have reduced downtime as well as operational costs.

Advanced reporting capabilities lead to simplified compliance with regulatory requirements.

Mkwawa is on track to acquire the skills and ownership needed to fully leverage Maximo’s capabilities. This collaboration is helping us obtain accurate and reliable asset management and performance data.
Nicholas Kanyamala, Engineering Manager, Mkwawa

Customer

Mkwawa Leaf Tabacco Limited

Tanzania

Services

Highlights

  • Transitioned to predictive and condition-based maintenance
  • Improved asset reliability and plant availability despite space constraints
  • Enabled accurate data capture and asset visibility for better decision-making
  • Supported sustainability goals (energy, waste, emissions monitoring)
  • Reduced risk of unplanned downtime through proactive maintenance
  • Established industry best practices in asset management
  • Strengthened local team capabilities and asset management standards

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