Silver Fern Farms (SFF) is New Zealand’s largest red meat processor, operating 14 processing sites from Dargaville in the North Island, to Southland. With a turnover of $3.2 billion and a workforce exceeding 6000 employees, SFF is one of the largest companies in the country by plant assets. The company’s asset portfolio (as it relates to significant machinery risks) includes over 4500 machines, presenting significant potential risks due to the sheer number of machines involved. SFF needed a comprehensive understanding of their machinery risks across all locations. Although risk assessments had been conducted, they were inconsistent in standard and formats, scattered across multiple file locations, with no centralised database. This lack of standardisation hindered the development of effective risk-based improvement plans. The goal was to have all plants and machinery risk assessed according to AS/NZS 4024 / ISO12100 standards. The data needed to be in a practical format that could efficiently manage the vast number of machines distributed across multiple locations. A data-centric approach was required to efficiently manage the risk reduction program.
TEG Risk had previously completed machine safety assessments for SFF on specific assignments, and smaller areas within the business. SFF was aware of TEG Risk’s capability to assess a large portfolio of machines cost-effectively and timely, using a custom application developed for other large red meat industry clients. At the time of this work undertaken with SFF, TEG Risk’s software had advanced to become third-party ready, a cloud based, interactive solution for managing a database of risk information MinRisk.
Given TEG Risk’s extensive experience with large assignments, we were able to accurately estimate the number of machines and provide a budget and time estimate for the project. It was estimated that the work would take 18 months. During this time TEG Risk was to complete summary machine risk assessments on over 4000 machines using MinRisk. The process would involve several key steps, including establishing client-specific terms and integrating them into application lookup fields to meet SFF’s needs. Our team then collaborated with SFF to determine a representative set of remedial work budget costs for capital planning, provided a Risk Reduction metric to prioritise risks based on reduction potential and cost, and worked with HRA Solutions to incorporate new features into the application, such as a report review and archive workflow, and developing client-specific downloads for PowerBI utilisation.
However the project was not without its challenges, as well as the scale of the undertaking, involving the assessment of 14 sites and 4700 machines (700 more than initially estimated), this work was carried out under substantial COVID-19 restrictions. As well as isolation protocols and testing, there were stringent PPE and hygiene protocols, and constantly changing government rules which impacted the accessibility and movement of both the TEG Risk staff and internal SFF team. To meet these challenges the team implemented processes to maintain quality and consistency while completing assessments concurrently across multiple sites. The outcome of which was that despite Covid related challenges, we delivered this colossal machine risk assessment project on time and on budget.
The data collated from this enormous machine risk assessment project, across 4700 machines, with 30,000 photo records of machine conditions, presented a challenge in terms of delivering the data in a coherent, accessible, usable and secure format. The data needed to be in a practical format that could efficiently interpret and manage the outputs from the vast number of machines distributed across multiple locations. TEG Risk leveraged their expertise and world-class safety software, MinRisk, to provide a comprehensive, data-centric solution to SFF. Key outcomes included SFF developing a comprehensive understanding of their machinery risks across all locations. For the first time the assessments were consistent in standards and formats, with a centralised database (MinRisk), and carried out according to AS/NZS 4024 / ISO12100 standards. The MinRisk software ensured cloud-based access to all risk assessments, enabling SFF to manage and access these records efficiently. With the assessments now standardised SFF were now able to develop more effective risk-based improvement plans. leading to a safer work environment and more efficient risk management processes.