Cutting tools are fundamental elements of the metal-cutting process. Depending on how the tools are chosen and applied, they offer the potential to maximize machining productivity or, on the other hand, create production bottlenecks. Much depends on how tool use is managed in relation to the overall manufacturing process.
Cutting tools are by their nature consumable; they wear until they are no longer effective. A traditional approach to metal cutting tool management employs wear analysis alone, focused on manipulating tool materials, geometries and application parameters to improve part output and tool life in a selected operation. Maximising the efficiency of a facility’s entire manufacturing process, however, involves consideration of broad range factors in addition to tool wear. It is essential to examine cutting tool wear or, more broadly, tool deterioration, in light of the overall or “global” manufacturing process.
Global Tool Deterioration Analysis (GTDA) goes beyond the basic measurement of tool wear to include tooling-related considerations such as time spent in tool manipulation, problems other than wear, production economics, shop organization, personal attitudes and assumptions, value stream management, and total manufacturing costs. GTDA is based on the regular evaluation of a large number of a shop’s used cutting tools randomly selected to construct a comprehensive picture of their contributions to the facility’s manufacturing efforts overall.
The Global Manufacturing Process
Study of tool wear usually is limited to a single tool employed in a specific machining operation. However, to gain maximum benefits, it is essential to examine tool wear or deterioration in relation to all tooling in a facility’s manufacturing processes. The manufacturing process begins with the acquisition of raw materials and planning that involves utilization of human intellect, technological resources, and capital investment. The process advances through value-adding and value-enabling activities but may be restrained by waste-producing events that result in the loss of money, time and intellectual resources and consequently reduce part quality and yield. The output is measured in terms of part quality, the quantity required and desired production time and cost.
Manufacturing Process Evolution
The methods used to analyze and predict tool life depend on the way in which the tools are applied. Over the centuries, manufacturing practices evolved from craft-level output of individual items to mass production of standardized parts. Improving manufacturing methods then brought about the second generation of mass production capable of producing increasingly greater volumes of similar parts – a high volume, low product mix (HVLM) scenario. Most recently, digital technology as applied in programming, machine tool controls and workpiece handling systems is facilitating the third generation of mass production that permits cost-efficient, high-mix low-volume (HMLV) production.
Although the key performance issues remain the same – namely achieving cost and time efficiencies, a certain minimum quality and a certain level of yield – second- and third-generation mass production techniques require different approaches to tool life analysis. In a second-generation HVLM scenario, identical parts are machined from the same workpiece material in production runs that may last days, months or years using the same equipment and the same kind of cutting tools. In that situation, tool life management is relatively simple. Shop personnel use prototyping and trial runs to determine the best average tool life, then divide the desired volume of parts by the expected life of individual tools.
Consistent tool life expectancy data enable a shop to plan tool changes that maximize tool utilization and support continuous production. However, HVLM production methods are declining in prominence.
To balance part inventory with demand and accommodate ongoing engineering changes, manufacturers are machining fewer and fewer parts in long, unchanging production runs.
At the same time, third-generation HMLV mass production strategies are growing in acceptance. Rapidly adjustable HMLV processes match well with contemporary inventory and engineering goals, but the planning process is much more complex. A run of ten parts may be followed by part lots of two, five or even a single component. Workpiece materials may change from steel to aluminum to titanium, and part geometries from simple to complex. There is not enough time available to determine tool life through trials.
In such cases, a workshop typically makes a conservative guess regarding a tool’s projected life and, to be safe, employs a new tool for each run then discards it well before the tool reaches its actual productive lifespan. A more global approach to tool wear analysis and predictions can help minimize waste of cutting tool capability.
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