Lean manufacturing (LM) has spread to all continents and to all business activities since Wornak, Jones, and Roos published a book titled 'The machine that changed the world' in the nineties. It also spread to agribusiness, not only to optimize the improvement of the machinery but also in the planning of the work, control of all production stages, times, tasks, costs, etc.
Fairtrasa Peru is undergoing a restructuring under its new administration. "Our commitment to the sustainability of small agriculture drives us to seek more efficient methods for our operations to obtain greater benefits using fewer resources," stated Yesy Lalupu Valladolid, the manager of the company. "This restructuring is focused on management by key performance indicators (KPI) and greater investment in innovation. To achieve this, we had co-financing of PROINNOVATE to implement the lean manufacturing work philosophy project."
"The implementation of LM in Fairtrasa began with the Value Stream Mapping (VSM) tool, which consists of identifying and eliminating those activities that do not add value and establishing the KPIs that ensure continuous improvement (Kaisen ). To do this, we needed to digitize the field, harvest, and postharvest processes, so we hired AGOTEC to use its platform and mobile application to collect, systematize, and analyze traceability data, quality control in the field and destination. We also implemented other tools, such as Jidoka, JIT, Kambas, Hoshin Kanri, 5S, Poke Yoke, Andon, and Smed."
"Evaluating the value chain using metrics and VSM allows us to focus on the economic costs and income for the company as well as on social and environmental aspects. That's why we decided to include our suppliers, the farmers, in this process. We want to help them improve the quality of their crops by reducing discards with adequate quality monitoring in the field and the efficient use of resources while allowing our clients abroad to visualize the different links in the supply chain."
"The project has allowed saving time and reducing resource waste by up to 15%, digitizing 90% of the quality and traceability formats, and -most important- it will allow us to count on big data to advance in the development of predictive models," the manager said.
For more information:
Fairtrasa
www.fairtrasa.com