Just-in-Time vs. Just-in-Case

A supply chain is often a very complex network involving many different stakeholders and processes that are critical to any business’s success. Effective supply chain management can help organizations to improve their efficiency, reduce costs, and enhance customer satisfaction.

 

As supply chains become more global and interconnected, they can become increasingly complex, making it difficult to manage and optimize them. Changes in demand, supply disruptions, and other factors can make it difficult to predict and plan for future needs.

 

This was emphasized by the significant impact worldwide of the COVID-19 pandemic, which brought widespread disruption to manufacturing, transportation, and logistics, as countries restricted travel and closed borders to prevent the spread of the virus.

 

This led to delays in the movement of goods and disruptions to the flow of raw materials, components, and finished products. Many companies struggled to keep pace with changing demand and supply chain disruptions.

 

As a result, many organizations have moved from a just-in-time (JIT) supply strategy to a just-in-case (JIC) approach.

 

In a just-in-time (JIT) strategy, materials and components are ordered and delivered to the manufacturer just as they are needed in the production process. This minimizes inventory costs and maximizes efficiency by reducing the amount of waste. JIT also helps to reduce the need for large amounts of warehouse space and reduces the risk of stock becoming obsolete.

 

For a just-in-case (JIC) strategy, companies maintain higher levels of inventory to ensure that they can meet customer requirements even when faced with unforeseen events such as unexpected increases in demand or supplier disruptions. This strategy aims to minimize stockouts and lost sales, but it increases inventory carrying costs and the risk of stock becoming obsolete.

 

In the pre-COVID period, companies made the choice between JIT and JIC depending on their specific needs and their supply chain considerations. For example, companies with products with high demand variability, long lead times, and high costs of stockouts tended to prefer a JIC strategy. On the other hand, companies with steady demand, short lead times, and low stockout costs preferred the JIT strategy. There were also organizations that blended both strategies to optimize their supply chain.

 

The supply chain disruptions because of the COVID pandemic have eased, but not to the extent where supply chains are back to pre-COVID levels. It is likely to take two to three years to return to previous levels.

 

Additionally, disruptions have continued since the pandemic, with the World Economic Forum identifying five key issues that caused added challenges in 2022: rising inflation, labor unrest, energy shortages and rising energy costs, geopolitical uncertainty (not least the ongoing conflict between Russia and Ukraine), along with extreme weather events such as flooding and hurricanes that affect key trade routes.

 

In response to these ongoing challenges, companies have sought to reduce their dependence on global supply chains and increase their ability to respond to disruptions.

 

In many cases, this means that manufacturers have been overbuying stock, parts, and labor, in order to prevent further disruption and avoid expensive downtime.

 

For example, when manufacturers can’t obtain the item they need, they may put a new purchase order in for double the volume — or more — hoping that will sway the seller to deliver faster. Then, when the order does come in, there is an excess in inventory.

 

Keeping stock in the warehouse, just in case, is a big expense on the balance sheet of any organization. Nonetheless, the level of disruption in recent years has meant that companies feel the need to do just that.

 

For those working in the oil and gas sector, the expense involved in a JIC supply strategy justifies a greater investment in technology to mitigate costs and avoid the unplanned downtime and unplanned repairs that make such an approach necessary in the first place.

 

Today, the relative cost of downtime and repairs is much higher than it was several years ago, so the likely return on investment (ROI) of condition monitoring and analytical equipment that prevents unplanned events is also favorable.

 

Oil analysis uses a combination of techniques, such as spectroscopy and particle counting, to analyze lubricating oils and other fluids used in industrial machinery. This analysis can detect the presence of contaminants, such as metal particles and water, as well as the wear and tear on machinery components.

 

Regular oil analysis can help identify potential problems with machinery, such as wear and tear, contamination and other issues, before they cause significant damage or lead to failure. This can help reduce unplanned downtime, which, in turn, has a significant impact on the plant's production and supply chain.

 

By detecting problems early and scheduling maintenance or repairs, oil analysis can help increase the reliability and availability of the plant. It can also identify the root cause of problems, preventing similar issues from occurring in the future. For example, if a problem is caused by a specific type of contamination, oil analysis can help identify the source of the contamination and allow plant operators to implement measures that prevent it from happening again.

 

The insights into equipment wear gained from regular oil analysis can also help in predicting the remaining life of the equipment — allowing operators to plan for replacement or maintenance in advance and avoid unexpected equipment failure.

 

Ensuring that the plant is using the correct lubricants and fluids, helps to extend the life of the equipment and reduces pressure on the supply chain by providing early warning of when the lubricant needs replacing.

 

Outage certainty is a key consideration for plant operators. When the plant is shut down for essential maintenance and any planned repairs, those operators need to be sure it is at the right time.

 

In terms of supply, this means making certain all the materials, labor, and resources are in place to ensure a successful turnaround.

 

The most effective way to deliver the insight needed for outage certainty is through condition monitoring and looking at the health and performance of equipment and systems in oil and gas plants in order to detect and diagnose potential issues before they lead to failure.

 

Oil analysis is one key factor, but condition monitoring can also include vibration, temperature, and other parameters. Continuously monitoring allows operators to detect early warning signs of impending failure and schedule the necessary maintenance or repairs before an unplanned outage occurs.

 

This leads to greater certainty for the plant operation and turnaround, as plant managers look to schedule maintenance and repair works during planned outages and, crucially, ensure the necessary parts are available and in stock ahead of the shutdown.

 

Oil analysis technology can support this by enabling operators not only to detect developing problems with equipment, but to nurse that equipment until the next scheduled downtime. This insight means that even when plants are aware machinery needs repair or replacement, they can ensure it keeps operating until the next scheduled turnaround. Instead of avoiding unplanned downtime, it creates planned downtime.

 

While this approach does not avoid the problem, it recognizes and handles it with minimum disruption.

 

Conclusion