In the food manufacturing business, safety and efficiency are two crucial ingredients for success. Adhering to safety standards requires access to actionable insights, in the same way that automation is key to eliminating bottlenecks and boosting productivity.
Indonesia’s Freyabadi Indotama, a chocolate manufacturer and supplier to various markets, previously relied on manual processes and complex systems. One of the company’s persistent challenges was its production schedule planning.
“Production schedule planning is time-consuming, requiring comprehensive consideration on work centres, product characteristics, incoming orders, and resource allocation. It is difficult for a planner to create an optimal production schedule while factoring in the physical parameters of the product to minimise changeovers,” remarked Adi Christian, the company’s Project & Engineering Manager.
Compounding the issue, adjustments were often needed due to machine downtime, material shortages, or unexpected customer orders.
Wrapped in paper
In the past, the chocolatier relied on spreadsheets to schedule production orders, but this approach came with a significant drawback — it required specialised knowledge from the planner.
“When there is a change in order or production constraints, the production sequence must be updated manually. Additionally, we did not have accurate visibility on when an order would be completed,” Christian explained.
Freyabadi Indotama also recorded material usage on paper, which was later inputted into the ERP system by an admin. This process was not only time-consuming and repetitive but also prone to errors.
Recognising the challenges of quickly implementing a manufacturing execution system (MES), the company opted to use Siemens’ Mendix low-code app development platform as a preparatory step.
“By implementing Mendix and automating processes linked to the ERP, we reduced the order creation process from 30 minutes to less than five minutes and saved approximately 500 man-hours per month on related data input and generation tasks. Production output visibility, which previously required two days from the time the order was released, can now be achieved within one shift,” Christian noted.
The company also adopted Siemens’ Opcenter Advanced Planning and Scheduling (APS) software. According to Christian, this solution addressed several requirements, including multiple-constraint scheduling, schedule statistics, what-if simulations, and linking viewers between orders, stock, and products in various stages of completion.
Taste test
As with any new solution implementation, Freyabadi Indotama experienced a teething phase during its adoption of Siemens’ platforms. Initially, the master data was not fully updated, and some activity scenarios were not captured during development because they occurred infrequently.
Moreover, work orders linking semi-finished goods to finished goods through work centre routing, as well as the splitting and combining of production batches, required further refinement.
“Working with reworked products or their handling procedure was also a challenge. We had to create a custom procedure in the scheduler and Mendix platform, as new work orders were needed to progress the production step to the finishing stage,” Christian recalled.
One of the company’s biggest challenges, however, was on the manpower side. Freyabadi had to upskill its operators to use the new systems and encourage a shift in working practices to ensure data was captured accurately and promptly. According to Christian, this was a valuable step in preparing operators for digital transformation.
“Having a backup team was essential to ensure continuity. We needed one team to move forward with the process and find and resolve issues, while the other cleaned the input data,” he added.
The implementation process was also a learning experience for the Siemens team, acknowledged Alex Teo, Managing Director and Vice President, South East Asia, Siemens Digital Industries Software.
“Freyabadi Indotama’s preference for specific technologies provided us with an opportunity to demonstrate our flexibility and open approach to integration, ensuring compatibility and overcoming potential technology mismatches to foster innovation,” he said.
Freyabadi’s reliance on unstructured scheduling rules based on individual experience also became a key area of collaboration, Teo noted.
“Siemens and its partner worked closely with Freyabadi Indotama to formalise these rules and transform their scheduling processes into a structured and standardised framework. This created a strong foundation for smoother adoption and long-term operational efficiency,” he explained.
Sweet success
Freyabadi Indotama is currently fine-tuning the weight factors, evaluating results, and compiling KPI metrics for Opcenter APS, following its recent deployment. Despite being in the early stages, the company has committed to furthering its efforts in automation and digitisation.
“We will continue digitalising our manufacturing operations and processes, implementing an automatic production system and vertical integration with ERP using MES and an energy management system. Meanwhile, the demand for sustainability, net zero, and circular economy will continue to increase, and we are exploring the right technologies to achieve our green goals,” Christian said.
The chocolatier is also exploring more generative AI use cases across its operations. It plans to develop an internal model, drawing on insights from various departments, to enhance areas such as customer experience.
According to Siemens, a significant trend in the food manufacturing sector is the integration of digital threads, which connect every stage of production, from design to logistics.
“This seamless data flow allows for real-time feedback and optimisation, significantly improving processes and efficiency,” Teo observed.
Another innovation shaping the industry is digital twin technology, which enables manufacturers to simulate and refine processes or entire facilities before implementation.
“For example, Siemens’ use of a digital twin in its Nanjing factory resulted in a 20-25% productivity increase, demonstrating its potential for cost reduction and accelerated project timelines,” Teo shared.
In conclusion, Teo highlighted generative AI and sustainability as major forces driving digital transformation.
“Generative AI is transforming decision-making by leveraging real-time data for process optimisation, material usage, and error reduction. Sustainability is another driving force, with digital tools enabling manufacturers to minimise waste, energy consumption, and emissions. This ensures environmentally conscious operations while boosting efficiency,” he said.
