In Kenya, the industrial sector, a key driver for economic growth and development, has an exciting opportunity to reduce emissions, cut costs and improve outputs to remain competitive. After independent feasibility and viability studies were conducted, it was identified that collecting real-time data from machines on the factory floor by measuring the real-time current pulse – which tracks machine speed and uptime/idle time – creates a myriad of opportunities to dramatically increase factory productivity as well as efficiency.
Power Africa, a US government-led partnership, explains that the Kenyan power sector is a true success story in sub-Saharan Africa, primarily powered by hydropower and with strong leadership at the highest levels of government, long-standing participation of the private sector in generation, impressive growth in access, and a strong enabling environment for innovation in off-grid solutions.
For Large Power Users, primarily factories, the clean growth required to provide much-needed jobs in the industrial sector, while protecting against climate change, will require dramatic shifts towards efficiency and clean energy in the industrial sector. Innovating in this area, a Nairobi-based software company, Safi Analytics, has developed a software system that is designed for the challenges factories face in emerging markets – unreliable and costly electricity, voltage fluctuations, varying machines of different ages imported from different countries, as well as teams with varying levels of training.
The traditional pen-and-paper tracking used by most factories across emerging markets to manage energy and other key aspects of production hampers the clean growth that they so desperately need. Safi Analytics’ innovative real-time system empowers the teams within these factories – engineers, managers, and operators – with tools that support dramatically improved efficiency plus data-driven decision-making around the best clean energy options for their needs.
Across the 30+ factories using the Safi Analytics system in Kenya, the system has empowered engineers and managers to creatively use the Safi dashboards and configurable SMS alerts to achieve up to 20% improvement in energy efficiency and up to 10% improvement in productivity across their teams. These significant improvements fall in line with the country’s ‘Vision 2030’ initiative, which states that Kenya aspires to be a middle income, rapidly industrialising country and globally competitive by 2030. To achieve this, Kenya’s GDP must grow by $4-6 billion per year, which is a growth rate of ~10% per year.
CASE STUDY 1: PLASTIC
A plastics factory in Kenya uses the Safi system daily to monitor the timing, usage, and settings of their machines for optimal production. Each morning, management reviews overall stats and detailed machine data from day and night shifts, catching excess idle time or abnormalities to address problems early, prevent breakdowns, and eliminate waste. They use Safi ’s data on efficiency of machines and operators for planning and costing. With Safi, they have improved labour costs by 10% and energy cost of production by 20%, achieving more than $100,000 per annum in savings.
CASE STUDY 2: PACKAGING
A packaging factory used the Safi system to reduce machine idle time during the night shift from up to 4.5 hours to under 30 minutes on average. With the system, the team was able to track uptime and idle time of machines down to the minute, and get real-time SMS alerts for any idle time or machine changeovers going beyond specified times. This has not only dramatically increased the factory’s productivity, but also saves energy wasted by idling, unproductive machines.
CASE STUDY 3: PAPER
A paper/printing factory is reducing energy waste and peak demand charge through the Safi system. Thirteen teammates at this factory use the platform daily to remotely manage production shifts, lower peak demand cost by 17%, and reduce nonproductive energy use by 15%.
The team can now:
- Check on production remotely to ensure shifts start and end on time
- Closely manage peak, adjusting machine settings and startup times to reduce peak 17% and monitor closely to sustain the improvement
- Identify and eliminate energy waste, already reducing non-production energy use by 15% through identifying machines drawing unexpected current
- Closely manage kWh/tonne
As digital technology advances – as seen in the above case studies – it becomes evident how one platform can be used across sectors to assist organisations in effectively managing their energy consumption and costs. Digital platforms and analytics are key to ensure an organisation minimises costs and maximises productivity, while consistently decreasing emissions and environmental impacts. This trend will surely extend beyond the borders of Kenya, ushering the African continent into a new era of digital efficiency.