When it comes to manufacturing, productivity is synonymous with money. It affects costs, profitability, and your competitive advantage. In an increasingly tough global marketplace, having a competitive edge can be a make-or-break factor.
Improving manufacturing productivity has been a longtime goal for most companies, but despite investments in productivity solutions, many still don’t have confidence in their efforts. And it’s easy to understand why. Companies often lack fully standardized, reliable ways to ensure that:
In simple terms, manufacturing productivity is the ratio of output to input – in other words, how much a company can produce based on a given amount of input – and it focuses mainly on throughput and quantity. Input covers factors including labor hours, capital resources, and natural resources, while outputs are normally measured by the quantity of goods produced.
But manufacturing productivity entails more than just a simple ratio. Evaluation criteria might also include a focus on functional issues, technology requirements, vendor considerations, and implementation and service concerns.
Many companies have invested in continuous improvement (CI) initiatives and various types of manufacturing software that measure or improve productivity. Even with these investments, however, most CI teams find they need to focus on gathering, harmonizing, and analyzing their data.
Software with prioritization and IOT capabilities gives a consistent and standardized view of which improvements will have the most significant impact on manufacturing productivity. Despite this functionality being available in many software offerings, it is yet to be widely adopted.
Today, technology solutions go beyond measure performance with real-time data; they can also rank opportunities for improvement. By seeking prioritization opportunities that are based on 100% of production-loss data, you can confidently focus resources and attention in the top issues, which can be challenging with traditional manufacturing intelligence, overall equipment effectiveness (OEE), or dashboard software.
In addition to prioritization opportunities, you should seek out solutions that perform root cause analysis for each problem. This ability to deliver deeper insights into root causes can transform challenges into opportunities. By understanding which constraints should be top of mind, and the scenarios when they are occurring, you can better understand the root causes of bottlenecks and work to eliminate them.
It’s important to find a system that can support multiple user profiles, including:
When all these roles use the same application, it fosters collaboration and eliminates bias and mistrust. PTC’s ThingWorx Digital Performance Management (DPM) extends full transparency across the manufacturing floor, giving you the power to understand your vulnerabilities and act proactively. With DPM, organizations can compare and set priorities based on the single metric of time, meaning they can recapture their lost production hours and increase effective time by over 20%.
Heightened demand is driving the need to increase and better utilize capacity – meaning manufacturers are facing unprecedented pressure to remain competitive, focus on continuous improvement, and pinpoint productivity losses.
Most manufacturers are in competitive markets with supply chain challenges. With so much out of the manufacturer’s control, it’s vital to leverage production resources such as facilities, equipment, people, materials, and tools effectively. Today’s environment of great uncertainty makes this more complex and crucial to success.
Calculating where to focus to stem those time losses is not straightforward since many sources of waste contribute to throughput and productivity losses. CI is a common process manufacturers use to identify and eliminate waste to improve performance. Lean, Six Sigma, and Operational Excellence are all examples of CI programs that can feed success – particularly if they have digital and analytics support.
Productivity is chiefly concerned with minimizing losses – and lost time is the simplest and most absolute way to measure those losses. The impacts of lost time are not just on the production operation itself. Time losses can be quantified in terms of impact on profit and customer service.
Capacity-constrained companies can only sell as much as they make, so it’s a top-line issue for revenue. For these companies, it also determines when they can promise and fulfill orders to customers.
Even when not capacity-constrained, time losses can impact costs and customer satisfaction. In some cases, companies could lower materials, assets, energy, quality, compliance, and payroll costs.
There are many ways to boost manufacturing productivity. While many of these options are long-term organizational changes, they are proven to be effective in improving performance and cutting costs.
A skilled workforce is a productive one. Employees who are knowledgeable make fewer mistakes, can be flexibly allocated where needed the most, and thrive in a positive workplace environment. A commitment to training helps retain employees as well, meaning you’ll reduce the cost and production impact of churn.
Maintaining an organization’s physical assets, such as equipment, plants, or facilities, helps maximize their lifespan, reduce downtime, and improve quality and efficiency. An effective and planned program of enterprise asset management will reap measurable productivity dividends.
Reviewing your full workflow – every process and step that is needed to get a product to the customer – is essential to understanding where productivity can be improved. Workflow revisions are constant, and they should be an ongoing exercise in your CI efforts.
Waste – actions that don’t provide any value to the product or customer – should be the target of CI efforts, but it’s often difficult to pinpoint its source. Reducing a manufacturing floor’s waste can lead to significant improvements in performance.
Increasingly complex production methods and global supply chains can make seamless coordination a challenge. Thorough communication and visibility throughout the process minimizes the risk of mistakes and interruptions.
Most manufacturing equipment isn’t used to full capacity. Metrics like OEE enable manufacturers to understand their equipment’s true capacity, allowing them to improve utilization rates and overall productivity.
Industry 4.0 and technologies powered by the Industrial Internet of Things (IIoT), Artificial Intelligence, and Machine Learning are helping manufacturers tackle countless productivity challenges, such as supply chain disruption and a growing knowledge gap among workers.
IIoT-driven technologies can help you determine where you are losing the most production time, so your CI team will know both where to focus and the likely results on a unit, line, facility, or even the entire production network. Once you know where you’re losing production hours, you can put them to use in the way that works best for you, such as adding production volume, reducing overtime shifts, cutting back on waste, or delivering the cost reductions your company needs. Additionally, by driving productivity and measuring KPIs such as production efficiency and reduced scrap, a digitized CI program can help your organization realize a dramatic increase in sustainability.
Volatile and unpredictable markets are pushing manufacturers to explore various ways to improve performance and reduce costs. Manufacturing productivity is fundamental to these efforts. Today’s digital solutions have made it easier than ever to identify and drive productivity improvements. While quick fixes are unlikely to solve manufacturing concerns, tangible improvements rely on consistent effort and ongoing analysis.
Consider whether your current investments for manufacturing productivity improvements are genuinely delivering a view that helps you prioritize opportunities in consistent business terms. Then, by setting objectives and goals for investing in a new solution, you can evaluate the possible solutions in all dimensions of your manufacturing organization.
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