Production & Process Optimization in Manufacturing
Mar 11
The use of process improvement techniques is essential for optimizing manufacturing processes. Optimized processes lead to greater efficiency when done correctly. What is the connection between the two? And why is process optimization so crucial for achieving greater efficiency?
Effectiveness is the answer to this question. It's not enough to have many things being produced. Producing finished goods requires a careful balance of tasks, checks, adjustments, and motions.
This is often referred to as a "path to continuous improvement". In most manufacturing operations, that path centers around the machine. As a result of habit and training, people interact with their machines, such as operators, mechanics, and technicians. Almost all of their efforts are aimed at ensuring maximum uptime. In the end, what matters is the effectiveness of their actions, regardless of whether they are manual or electronic. Optimizing a process makes that interaction more effective by making adjustments.
Producing finished goods requires a careful balance of tasks, checks, adjustments, and motions.
IMPROVE EFFICIENCY
What is Production Optimization?
The goal of production optimization is to increase the productivity of the production system through a number of activities. A process optimization effort focuses on improving the efficiency of a finished product during its stages as opposed to a product optimization effort focused on improving the efficiency of a finished product.
The goal of production optimization is to increase productivity by using models, analysis, prioritization, and measurements. Equipment, staging areas, inventory protocols, facility layout, and conveyance are all part of this optimization process.
Production optimization is common in industries with large footprints, such as oil production and gas construction. Almost any production process can be optimized to increase value in a manufacturing operation.
Since IoT technology has matured, companies have discovered that real-time data analysis provides them with insight into changing conditions and flow of the system, allowing them to boost productivity. In order to optimize production rates in the entire production process, companies must use these insights.
THE FOLLOWING AREAS
Can Be Optimized for Greater Value Through Insights:
The product itself is the focus of many companies focused on "process improvement" technology. However, work in progress can have a significant impact on productivity. When inventory is tied up for too long, it can have a negative impact on cash flow and may create taxation problems. Moving products from station to station unnecessarily may increase labor costs due to multiple moves.
Auditing workstations: Since interactive dashboards and factory boards have become more digital, the placement of these HMIs may need to be reconsidered. It may make sense in a manual tracking environment, but in a digital environment, it may result in increased workloads or reduced effectiveness. Low-profile devices such as HMIs, screens, monitors, and others can improve productivity.
There is often dead space in manufacturing that houses WIP that has nowhere to go. The more handling there is, the higher the operating costs will be.
Work stoppages can result from bottlenecks in upstream production processes. It may be necessary for managers to address a bottleneck resulting from the increase in output of some factory monitoring platforms.
In order to increase production, technology will enable warehouse and inventory protocols to be improved based on real-time inventory data that highlights problems and prescribes solutions. New environments require effective communication to ensure the flow of materials.
Making changes to optimize production performance and lower costs is part of the journey to digitization and data-driven production. The power of an IoT-driven production monitoring platform may require companies to change the factory layout or move machines to take advantage of the technology available.
The Difference Between Process and Production Optimization
It is important to note that process optimization eliminates unnecessary steps within the production system, as opposed to production optimization. Essentially, it's a process optimization technique that increases efficiency for a specific step or sub-process in order to maximize production optimization. Production optimization, on the other hand, aims to optimize the system as a whole. A real-time model can be used to analyze flow rates, machine layouts, labor utilization, and other factors to optimize a production system's physical performance.
Process optimization will include steps such as:
Identifying process-specific problems
In order to achieve the desired state, the current state must be analyzed
To determine if the change was successful, audit the change
Keeping track of the change
Production optimization will include steps such as:
Layout change in a factory
Equipment and tools are changed or rearranged at the point of use
New procedures for work in progress
Training operators and technicians to respond to automated alarms and eliminate old habits by understanding the monitoring system
Establishing new internal delivery procedures for inventory
Analyzing the layout of monitors and HMIs
IMPROVED
Machine Uptime
A manufacturing manager's worst nightmare is downtime. In addition to dealing with its consequences, many people spend much of their time managing its causes. Data-driven approaches can reduce downtime and increase equipment uptime for a company.
By analyzing and ranking the top causes of unplanned downtime in the production process, this can be accomplished. In turn, this information can be used to adjust processes in order to reduce or eliminate many types of downtime. Due to the order of the list, the most egregious culprits can be tackled first.
Managers can then proceed methodically down the list, adjusting process parameters as needed to bring each item into compliance with requirements once uptime has increased and stabilized. In order to prioritize what needs to be addressed first, clean, clear data is key to this list and ranking.