The manufacturing arena grows more complex and competitive by the day, with businesses keen to eke greater efficiency from their processes and edge out the competition. And technology has a big part to play in this, with emerging systems and methodologies enabling manufacturers to scale their operations like never before.
For SMEs or those new to manufacturing, staying abreast of the industry and its ever-changing landscape can be challenging. To help, we’ve put together this glossary of key manufacturing terms, many of which relate to enterprise resource planning and the adoption of efficiency-boosting processes.
A form of manufacturing that facilitates rapid response times and improved flexibility through tools, techniques and initiatives. Agile manufacturing is about responding to the needs of customers, clients and the market on the fly, enabling a business to respond to changing requirements in such a way that minimises lead times.
Shown as a percentage of the overall production time, availability is the time a machine is available to manufacture products. Businesses can calculate an individual machine’s production availability through collecting and analysing data throughout the production cycle, which is then fed into an ERP-supported analytics platform to give a percentage figure.
Cellular manufacturing falls within the remit of several different manufacturing strategies, including lean, agile and continuous. The ‘cell’ concept promotes continuous improvement on the factory floor, with equipment arranged in such a way as to enable shorter production times, increased efficiencies and greater process control over every stage of the production cycle.
Continuous-flow manufacturing is a specific type of production whereby raw materials undergo continuous motion and change on their way to becoming an end product, i.e., through mechanical, thermal or chemical treatment. As you might expect, continuous-flow relies on a water-tight supply chain, so advanced management software is a must here.
Cycle time is one of the primary key performance indicators of many manufacturing processes, used to make calculations and analyse a plant’s performance. Many manufacturers rely on cycle time to inform their ERP system, which features unique applications that can calculate factors such as production cost and scheduling, and automate supply chain purchasing.
Another important KPI that is fed into ERP systems; downtime represents the amount of time a machine, line, cell or process is out of action on the factory floor. As with cycle time, this figure is used to calculate a range of factors, including the performance, cost and efficiency of production.
Industry 4.0 may sound like a marketing buzzword, but it’s an expression that captures the shift towards smart technologies that’s occurred within the manufacturing sector over the past five years. In the same way Industry 3.0 was used to herald the internet’s impact on manufacturing, Industry 4.0 is viewed as the next phase in the digital revolution.
Lean manufacturing is a concept that aims to eliminate waste, optimise processes, cut costs, and boost innovation throughout the production cycle. Through the application of lean practices and methods of production, as well as investment in next-gen management software, manufacturers can enjoy the many benefits that the lean practice brings to the table.
Mean Time Between Failures (MTBF)
Another KPI used to measure production performance; mean time between failures (MTBF) is used to calculate the average time between equipment faults and errors that interrupt production. Every manufacturer has its benchmark MTBF, and when the figure starts to creep higher, it’s time to take action before consistent failures impact production scheduling.
Overall Equipment Effectiveness (OEE)
Developed by legendary Japanese car manufacturer Toyota, overall equipment effectiveness (OEE) is a manufacturing metric comprised of several KPIs within the production cycle. OEE encompasses availability, performance and quality, giving a percentage sum that can be invaluable when evaluating machine effectiveness and the overall efficiency of the factory floor.
A concept coined by Italian economist Vilfredo Pareto, the ‘Pareto’ principle is used to analyse downtimes within manufacturing, providing insight into the issues affecting performance. Pareto argues that 80% of consequences come from 20% of causes, meaning that businesses must regularly assess internal processes if they’re to find the 20% of problems affecting efficiency.
One of the KPIs used as part of the Pareto principle; performance is a percentage metric used to calculate actual cycle time against ideal cycle time, so that businesses can ascertain accurate scheduling and delivery times. Calculating performance relies on advanced analytics software, which unifies data across different machinery and processes.
Typically associated with lean manufacturing, the term Poka-Yoke is derived from the Japanese term for ‘mistake-proofing’. Poka-Yoke is concerned with eliminating errors from production cycles, ensuring minimal machinery faults and the reduced risk of final product defects. The concept is particularly good at picking up and reducing human errors, which are among the biggest drivers of manufacturing inefficiency.
Programmable Logic Controller (PLC)
A programmable logic controller (PLC) is a computer that’s programmed to work as part of a cellular manufacturing workflow. An important facet of the manufacturing ERP ecosystem, PLCs automate, monitor and assess processes throughout the production cycle, preventing defects and faults as and when they appear.
Another metric that feeds into the Pareto principle; quality is used to measure products created by an individual machine, a cell, or a full manufacturing process. Manufacturing analytics tools measure quality by collating ‘reason codes’ – the unique digits assigned to different faults and defects within a production line.
Six Sigma is a method of manufacturing that places quality and efficiency at the heart of the operation, with data-driven processes and methodologies to eliminate defects and drive efficiency. The concept of Six Sigma states that a process mustn’t produce more than 3.4 defects per million opportunities, which is considered the optimal rate for long-term efficiency.
Statistical Process Control (SPC)
Statistical process control (SPC) is when statistics are used to determine production issues. SPC relies on consistent and accurate data gathering and analysis, from which solutions are developed to reduce inefficiencies and flag up potential production issues.
Shown as a percentage, utilisation refers to the total capacity of a production cycle. It measures how much capacity is being used at a given time, whether on a specific piece of equipment or throughout a manufacturing line – providing a means of accurately measuring production schedules and delivery times.
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