Point of View

Optimize manufacturing processes by finding the “golden batch”—before spending big on digital

March 24, 2020

Manufacturers must get the basics of process optimization right before going down the investment rabbit hole on emerging technologies such as AI or analytics. As these technologies start to facilitate predictive maintenance, supply chain analytics, and new revenue streams, manufacturing must also strive for excellence in its day-to-day operating practices. Manufacturers’ efforts can achieve immediate efficiency or quality improvements while execs simultaneously plan longer-term transformation projects. An increasingly popular and relatively simple method of finding quick, but potentially big, wins in manufacturing processes is “golden batch” analysis—answering when and why a manufacturing process performs at its best, and how to replicate it as often as possible.

 

Golden batch analysis is a common offering among manufacturing service providers (or at least a capability in their Industry 4.0 toolboxes); a recent play in the market saw LTTS launch its “Industry 4.NOW” framework. As analytics and the industrial internet of things (IIoT) develop, benchmarking processes to find a golden batch becomes more effective and efficient, as does eliminating bottlenecks and addressing the root causes of poor performance. While LTTS is not alone in offering to find golden batches, it does fall into a small category of providers that differentiate the process industry from the rest of manufacturing; HFS has previously called for providers to better address the unique challenges facing the process industry given that they make up over 50% of the £35 trillion global manufacturing output.

 

Looking at our manufacturing exec community in Exhibit 1, we can see that any solutions that tackle operating costs will grab their attention. But, before manufacturers spend big on services and technology to optimize their processes, they might find that their golden batch is far simpler to assess, as the cement industry, in particular, is beginning to realize.

 

Exhibit 1: Operating costs dominate manufacturing execs’ priorities

 

Which of the following are C-suite initiatives? 

 

Source: HFS Research, State of Operations and Outsourcing, 2019. N=53 manufacturing executives

 

 

Beyond providers’ marketing material, cement and consumer goods manufacturers have already proved the value of golden batch optimization

 

In 2016, Cambridge University research found huge savings in the cement industry by following a golden batch methodology. Briefly, the research mapped out a cement plant’s average daily energy consumption, ranging from the 1st percentile (when it performed worst) to the 100th (when it was at its best). Analyzing the variation in performance, the research found that:

 

  • Oxygen content in the fuel mix to the kiln (the central part of the cement-making process) could be optimized to save 7% of the plant’s total energy consumption and 10% of its CO­2
  • Despite an initially slow uptake, the threat of climate change regulation and a carbon price before 2030 turned heads at the plant in question; the cement industry currently produces roughly 8% of global CO2
  • Further digging showed that this opportunity applied to manufacturing as a whole. In another case, through a similar method, a consumer goods manufacturer was shocked to discover it was burning far more gas than required—around 12%.

 

A fresh look at your manufacturing processes could be hugely valuable–productivity, efficiency, emissions: it’s a lot, but possible

 

The beauty of the golden batch method is that it doesn’t force manufacturers to nose-dive and risk a belly-flop. It only requires the necessary complexity and time. After finding any variation in your performance, you can quickly tell if it’s worth investigating deeper aspects of your operation to determine more intricate root causes.

 

Of course, some variation is inherent. There are times when you will naturally operate at lower or higher levels due to restrictions or mandatory targets. To start with, however, looking at high-level performance variation, without making allowances or excuses, can lead to surprising and often valuable lessons.

 

It seems obvious to state the need for manufacturers to optimize their core processes before embarking on a costly journey to Industry 4.0 or enterprise-wide digital transformation. It is staggering, however, what a company or even an entire industry can overlook when their focus is on other priorities—à la the cement industry.

 

It’s not too simple or too complex

 

We must dispel the concern that golden batch methods are too simple to be effective without sophisticated technology, or for certain processes, that they are too complex and time-consuming to attempt. These methods ensure you only use the time and complexity required—each phase proves the value of the next.

 

Some technology vendors will argue that golden batch analysis requires analytics or underpinning AI to achieve: you CAN go this way, but having discussed extensively with the Cambridge academics involved in the cement industry case, they, and we at HFS, feel this is widely achievable by employees with a reasonable top-level understanding of their operation… and access to the data.

 

The required degree of complexity will vary from process to process: The original work in the cement industry required energy modeling, but in that case, the incentive was (and still is) plain to see: 7% of the plant’s energy and if scaled up through the cement industry, approximately 1% of the world’s entire CO2 output! For the consumer products manufacturer, the system was simpler, and the pathway to implementation (and payback) was immediately clear.

 

Some consultants might say that this “first principles” or “top-down” holistic approach is applied in all their optimization studies. Certainly, more complex methods like Six Sigma also examine variation; however, golden batch is simpler and allows a high-level look without the need for expensive Six Sigma training; improvements can also be more quickly replicated at scale, as best operating practice throughout an organization. 

 

The Bottom Line: Don’t end up with a million-dollar AI program that gets lost in the weeds and forgets the simple stuff.

 

Every manufacturing process may not be able to make the same improvements as the cement industry. Nevertheless, a quickfire extraction of data and reading between the lines is worth a shot… before a million-dollar AI program sends you plummeting into the weeds. Any version of a wholescale digital transformation is an intense financial and time-heavy commitment, but with the right team, processes, and mindset, improving operational practice can happen overnight.

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