Beating the high production cost blues

LOCAL manufacturing firms continue to face blustering headwinds – from heightened global competition from the likes of China and India, to sluggish demand and macroeconomic conditions, to critical skills shortages and labour issues.

But technology can help to relieve one of the most common pain points that we’re seeing: the stubbornly high costs of production. By using the right digital tools, manufacturers can sustainably reduce their production costs, breathing new life into their margins and ensuring profitable operations.

Let’s look at three areas in which this can be achieved:

1. Raw material inventory and production planning

By using digital tags like radio frequency identification, plant operators can gain greater visibility into materials, equipment, parts and other assets. Combine this with other datasets to build up a very rich picture of materials as they flow through a factory to eventually become finished products.

By knowing exactly where everything is, it becomes easier to plan production, as data is automatically piped into one’s Manufacturing Execution System or Production Lifecycle Management System. This means faster logistics and greater throughput of products, as well as increased levels of uptime and productivity – ultimately driving down input costs.

Rapid advances around 3D printing means that certain parts and materials that are required urgently can be created on-site and at short notice.

One of the leaders in this space is General Electric (GE), reinventing itself with a variety of strategically-connected technologies – including lean manufacturing, additive manufacturing (also known as 3D printing), and advanced software analytics to enhance productivity. At Grove City, GE has used these technologies to reduce unplanned downtime by 10 to 20 percent, improve cycle time and reduce costs.

2. Predictive maintenance and predictive analytics

With sensors gathering key data on each machine – from humidity, heat, wear and tear, usage times, oil levels, and various other data points – we can start predicting when a machine is likely to fail, or require servicing.

Known as predictive maintenance, it helps to curtail the costs of managing industrial equipment, and reduces unexpected downtime (as services, repairs and refurbishments can all be scheduled to avoid interrupting production lines).

With some analysts’ findings suggesting that downtime costs the average factory between 5 and 20 percent of its productive capacity, predictive maintenance can be one of the most crucial weapons in the fight against billowing production costs.

But we can extend the principle of predictive maintenance to encompass predictive analytics across the entire factory operations. With predictive alerts flying in from all corners of the factory, it becomes possible to orchestrate the operations more dynamically, changing the daily plan.

3. Proof-of-concept

Creating a new prototype (for a particular product) was a lengthy and extremely expensive endeavour – particularly when the concept turned out to be the wrong one and never progressed into full-scale production.

With cutting edge digital simulations, 3D representations, and holograms, it becomes possible to play around with various new prototype designs – testing them with users and getting a tangible feel.

By creating sophisticated prototypes in these new ways, the upfront costs of producing a single unit on the production line are greatly reduced. As manufacturers evolve towards smarter and more digital production lines, it’s not always easy to know where to invest first, where one will get the loudest “bang for their buck”.

Focusing on these three areas, and building from these foundations and gradually connecting other technologies, manufacturers can address the most pressing pain points and set themselves well on the way to reducing the costs of production.