Schneider Electric > Case Studies > Preparing for a fully automated future

Preparing for a fully automated future

Customer Company Size

Large Corporate

Region

Asia

Country

Singapore

Product

EcoStruxure Augmented Operator Advisor
EcoStruxure Machine Advisor
Harmony Hub & Power Tag sensors
Compact NSX circuit breakers
Harmony Hub wireless gateway

Tech Stack

IoT
Data Analytics
Augmented Reality

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Cost Savings
Digital Expertise

Technology Category

Functional Applications - Remote Monitoring & Control Systems

Applicable Industries

Plastics

Applicable Functions

Discrete Manufacturing
Quality Assurance

Use Cases

Predictive Maintenance
Energy Management System
Factory Operations Visibility & Intelligence

Services

System Integration
Data Science Services

About The Customer

Sanwa is a plastics manufacturer established in 1977. The company has grown into an international presence that supplies Schneider Electric and car manufacturers in South-East Asia. They operate nine factories from their global headquarters at Woodlands East Industrial Estate in Singapore. Despite their success, Sanwa knows they are vulnerable to shifting market forces. Sensing opportunity, they began their digitalization journey in 2016 with two long-term goals: to digitalize and automate their factories, ultimately achieving zero defective parts per million for their clients. In doing so, Sanwa would gain efficiency and demonstrable business growth, especially when only 13% in the region have started Industry 4.0 transformations.

The Challenge

Sanwa, a plastics manufacturer in Singapore, was facing challenges due to regional competition, a dwindling labour supply, and rising operational costs. They saw digitalization as the solution to improve factory productivity, develop skilled employees, and dramatically boost energy efficiency. They started their digitalization journey in 2016 with two long-term goals: to digitalize and automate their factories, ultimately achieving zero defective parts per million for their clients. They started a pilot project with a single production cell as proof of concept for all their stakeholders. The first automation phase successfully showed that they could do more with the same manpower, with localized data collection. The next step in 2018 was to link more of such production cells together into a data network. Forming that data network was crucial for Sanwa for it determined all the necessary steps forward. Other than productivity, their chief concern was traceability and transparency—they were losing time and money on dated manual reports.

The Solution

Sanwa decided to build a 580 sqm model factory area within their Singapore plant in 2019. This new development covered their automotive components line, with consultation from Schneider Electric, iPlast 4.0, and other industry partners. Following field investigations and interviews, Sanwa adopted EcoStructure™ architecture to drive all their data collection and visual interfaces. Compact NSX circuit breakers were installed for their remote monitoring capabilities, allowing Sanwa to pinpoint energy consumption to individual machines. While these already have a SmartLink gateway, Sanwa is planning to implement Schneider Electric’s Harmony Hub wireless gateway during Phase 2 of its Digitalization Journey for comprehensive IoT coverage. This allows Sanwa to not only monitor energy consumption but also temperature, humidity, and pressure through a host of wireless sensors. iPlast 4.0 collects and analyses this data with an on-site manufacturing intelligence system, which is then relayed back to the operations team through other Schneider Electric solutions.

Operational Impact

Data analysis is now 80% live, and their production cells have been drastically transformed into fully automated cells.
They are now able to do more with the same amount of manpower as a single worker can oversee multiple cells.
Sanwa is training this freed-up manpower for more valuable positions, and the energy savings borne by machinelevel monitoring has translated into cost reductions for their customers.
They can also precisely factor in the cost of energy required to produce a single product unit and this has allowed them to accurately cost their products, thus giving their customers the optimal rates.

Quantitative Benefit