Spare parts management is not a new concept for manufacturing. Yet, due to global supply chain disruptions that started during the COVID-19 pandemic and have not abated, effective management of safety stock and critical spares is more crucial than ever. Robust management practices prevent financial losses, technician stress, and accumulation of excessive downtime.

Software solutions that help process and manage manufacturing robot data are becoming more prevalent. Companies can now use these solutions to mine the data for insights that will help facilitate parts coordination and assist with inventory control. With a firm grasp on parts inventory, companies can mitigate complications caused by global supply chain disruptions. This post will discuss the consequences of ineffective parts management, the importance of knowing which parts to keep on hand, and the role that new technology can play in helping companies do just that. 

The Consequences of Ineffective Parts Management

Ineffective parts management results in long lead times, high costs, and undue stress on certain roles in the organization. 

Long Lead Times and Shipping Costs

Expected breakdowns occur when a manufacturing facility experiences hardware deterioration due to weather, time, human intervention, old age, or other familiar sources.

If manufacturers haven’t already stored spare parts in expectation of failure, the parts must be purchased and acquired as quickly as possible to avoid downtime and loss of further production. But this is often easier said than done.

The COVID-19 pandemic extended lead times for mechanical hardware, instrumentation, electrical equipment, and other manufacturing necessities. Pandemic-induced factory shutdowns and global supply chain disruptions cause suppliers to struggle with sourcing and procurement. Now, purchasing lead times can range anywhere from one day to one year. Furthermore, overnight and next-day air shipping, for sometimes heavy pieces of equipment, can put maintenance departments significantly over budget.

Robot-as-a-service (RaaS solutions) can help companies avoid the weeks- or months-long waits for parts delivery—and the costs associated with expedited or bulk shipping. These solutions use real-time data to gain insight into the remaining lifespan of their equipment instrumentation. When manufacturers are aware of how long a part is likely to last, they can account for lead times, shipping costs, and appropriate budget periods. This integrated data is also stored and processed for long-term analysis to help with recurring predictions about spare parts needs. 

Unexpected Labor Strains of Improper Parts Management

Many technicians and mechanics take pride in their work and feel a personal responsibility to keep lines running as much as possible. Unexpected downtime is a source of stress for these roles, and becomes more pressing the longer the downtime persists. 

When mechanics lack spare parts to troubleshoot with, they have to come up with increasingly complex and innovative solutions to fix a problem. These complicated solutions take years of practice to perfect; technicians will need a lot of training and investment before they can accomplish such a task. Also, if a significant amount of troubleshooting is involved, technicians often will find that their judgment and ability are clouded by the stress of the situation, which further increases downtime.

Proper parts management and combining historical data with real-time supply coordination enables mechanics and technicians to troubleshoot their lines more easily. When parts are readily available for testing and diagnosing issues, resolving them is quicker and more cost-effective. Organizations will also save money because equipment downtime and unnecessary overtime will be reduced.   

The Importance of Critical Spare Management and How Data Solutions Can Help

Having the right spare parts on hand is ideal—but how can manufacturers know which are the right ones to keep in stock? Thanks to new technology, organizations can now identify critical spares, and which spares are the most advantageous to maintain in inventory. The critical spare is an expensive, hard-to-come-by, but absolutely crucial machine part. A critical spare part may or may not be something that breaks often, but is something that would cause a machine to take a line down for an extended period of time. In addition, these parts are often expensive and difficult to get on hand quickly.

Intelligent machines, RaaS, and Internet of Things (IoT) solutions all help engineers determine which parts constitute critical spares. Such data solutions, which identify what these critical spares may be on different cells of the manufacturing line, allow companies to stay ahead of the kinds of disastrous breakdowns that cause immense amounts of downtime. Companies can have more committed conversations with suppliers regarding expensive acquisitions, and suppliers can be aware of predictive information. Budgets will also benefit. Using this machine data, engineers will be able to forecast when critical spares should be purchased to account for long lead times or other supply chain restrictions.  

Avoiding Parts-Related Concerns With Modern Solutions

Using robotic solutions with increased capability in manufacturing environments avoids financial strain with proper parts forecasting, coordinating, and management. These solutions allow for real-time and historical data to help engineers model where machines are weakest in the quantity of failed parts and how crucial the failed part may be.

Reducing technician stress, labor overtime, long lead times, heavy shipping costs, and downtime that occurs when companies don’t have critical spares on hand are some benefits of implementing RaaS or IoT solutions in manufacturing plants. Keeping a finger on the pulse of aging manufacturing machines and what they may require is vital in successful manufacturing engineering environments.