Introduction

Preventing Parts Delivery Disruption through IoT

 

This case study from eMoldino illustrates how to preventing parts delivery disruption through 4.0 IoT technology.

  • Client

    eMoldino

  • Services

    To solve long-standing problems in supply chain management

  • Technologies

    Industry 4.0 IoT technology

  • Dates

    07/05/2018

PDF

Description

The following is the story of how one of eMoldino clients utilised Industry 4.0 IoT technology to solve long-standing problems in supply chain management – specifically, that of dealing with component parts disruptions, and reducing product time to market.

 

The bleeding neck

The client, who will remain unnamed, is one of the world’s largest information technology companies by revenue alone, with a market cap of hundreds of billions of dollars, and large market shares in electronic equipment.

 

The client thus creates manufacturing moulds, which, once produced, are distributed to their suppliers in over 40 countries. This globe-spanning capacity for manufacturing requires the client to maintain a top-of-the-line supply chain, which they had been trying to implement for years.

 

What they lacked, however, was an efficient data-gathering system for their moulds’ activity.

 

Like most other global OEMs, the client could not capture their moulds’ production data in a way that was accurate, up-to-date, and automatic. Instead, they had to retrieve and input this data manually, updating it daily.

 

The nature of any manual updating system makes its users vulnerable to human error. One mistake can lead to absent component parts, leading to disastrous disruptions in product assembly and millions of dollars in lost revenues and reputation damage.

 

The problems of manual data entry

Up until 2013, our client managed their moulds manually, collecting data on their in-house and suppliers’ mould activity and feeding it to their ERP systems manually. They identified three main issues with this system:

 

1. Inaccurate, unreliable data

Inaccurate data is the result of either intentional or unintentional data errors. Unintentional errors are human errors in gathering and inputting data. Data relevant to moulds includes shot count, cycle counts, and mould location.

 

Intentional errors are examples of bad habit manipulation, where suppliers deliberately report mould data higher or lower than the actual shot counts. Data is also infrequently up-to-date, as data tracking and uploading to company ERP/SCM systems does not occur in real-time.

 

2. Wasted manpower

Monitoring and recording mould data is as important as it is repetitive, tiring, and time-consuming. Talented individuals are forced to do these tedious, menial tasks, when they could have been allocated to procurement, product innovation, or any other profit-generating department.

 

3. Inefficiency of manual integration

Our client has thousands of suppliers, each using thousands of their moulds to mass-produce for them. Most times, these suppliers collect mould-related data, to be reported to the client manufacturer. For in-house production, the clients’ manufacturing teams manually gather what data they are able. The process of integrating all these separate pieces of data into one understandable whole is inefficient and time-consuming, even without considering the large margin for error.

 

A disaster waiting to happen

Beyond just its inefficiency, manual data entry carries a high risk for disastrous consequences. The chief ‘disaster scenario’ for our client was a complete halt in their production, resulting from a breakdown in the delivery of their component parts,

 

Imagine you are the head of large manufacturing company, with one million units promised to distributors around the world. The product’s marketing campaign is going swimmingly and high expectations abound in the market. Your job is to ensure that a million of your manufactured goods, whatever they may be, are ready for the deadline.

 

Then you receive that nightmare call, telling you that one of the myriad components required to make your product has not been delivered yet. Without it, the whole assembly process is delayed. Sales and marketing are in an uproar pointing fingers, and the deadline needs to be moved. The market’s expectations shift accordingly.

 

Not only has the company lost millions of dollars of revenue, but it has suffered potentially irreparable reputation and brand damage. The blame for it all rests squarely on your shoulders.

 

This scenario was what our client had in mind when they said they wanted clear visibility of their parts production data before their delivery dates. If they possessed the freedom and wherewithal to look over the shoulders of their suppliers or in-house manufacturing sites, they could take proactive action against any potential interruptions in their production.

 

In seeking this, our client sought a better, more efficient way to track the data of their moulds, mainly to identify which suppliers may not be able to meet the agreed delivery dates.

 

The answer was a wireless sensor that could relay their moulds’ shot counts in real-time. This sensor would link up with internal information systems, providing ease of use and easy integration. Data tracking of this sort would be accurate, up-to-date, and automatic.

 

IoT solutions in manufacturing

The client understood that a manual system of tracking hundreds and thousands of part producers with exponential five-digit moulds was next to impossible. Their solution was then to develop a manual data-gathering system with an automatic one.

 

In 2013, the first solution was developed via a partnership with Best Information Technology (BIT) and PSTEC (of which eMoldino is a spin-off company with exclusive global distribution rights of the product). This solution utilised IoT, and was wireless, online, and connected to their in-house database systems. The client placed this new system in the ‘shot counters’ attached to each of their moulds. These counters were mechanised, digital number counters that counted every time a mould created one unit of production.

 

With their moulds linked with IoT, the client could track their moulds in real-time, with information such as shot counts, cycle times, and location becoming clear and indisputable. With their ERP systems receiving this data directly, the client was finally able to forecast progress on their parts production.

 

Tremendous man-hours were saved, without sacrificing data accuracy and reliability. More importantly, the new visibility over supplier parts production significantly reduced the risk of breakage in component parts delivery. The client was quick to install the shot counter, christened eShotLink, to all of its moulds, achieving rapid improvements in their supply chain management.

 

The aftermath

The ‘wireless shot counter project’ is an example of our clients’ willingness to embrace new technologies to improve what was once overlooked as an area of non-interest. In this case, 4.0 IoT technology in manufacturing proved to be the next step for our client.

 

Two plus years of investment and large sums of financial and human capital were needed to co-develop eShotLink. The end result was a bold step towards data automation and IoT integration, solving age-old issues with the kind of forward-looking verve and daring that should be required of all modern manufacturers.

 

Case-Study courtesy: eMoldino, an industrial automation technology solution provider. The company manufactures the world's first wireless digital mould counter.

 

eMoldino

South Korea

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