Patrick de Vos (see PROFILE), Applied Machining Expert (VISIT GROUP), Seco Consultancy Services
All machining shops face the same task: converting raw material into finished workpieces. The products must be machined to the specified level of quality, completed in the required quantity and delivered within the desired amount of time. Sustainability considerations and environmental issues must be resolved as well. To remain competitive and profitable, shops continually seek the most economical and productive ways to accomplish their work.
The ultimate example of those process improvement efforts today is what is called in Europe “Industry 4.0” – strategy and tactics that integrate state-of-the-art data acquisition, storage and sharing technologies into the manufacturing process. Industry 4.0 is presently the top level of manufacturing evolution, requiring strong management commitment, specialised personnel and significant investment.
Figure 1: NEXT STEP – total integrated production model
Unfortunately, shops that lack the extensive resources of global industrial giants such as General Electric or General Motors may feel that productivity improvements are out of reach. However, simple, cost-effective analyses and actions can have a large positive effect on the productivity of small to medium-size operations. In fact, before investing in new computers, robots or personnel, any shop, large or small, should perform basic process analysis and organise current equipment and practices. The truth is that computerisation of disorganised shop operations results only in computerised disorder.
Three phases and ten simple steps
Organisation of shop practices begins by viewing the production process as three phases. First is a selection phase, involving choices of cutting strategy, tools and cutting conditions. The next phase is collection, in which the selected tools and strategies are grouped together in a machining process. Realisation is the third phase and puts the process into action.
In a large number of cases, the results of phase three fails to meet expectations, and certain steps are needed to bring reality in line with preparation. The steps can be technical in nature, such as seeking ways to moderate cutting forces, or economic, including actions to reduce costs. Fortunately, there are ten simple steps that will enable a shop to analyse and improve its metalworking operations. They are as follows.
Intelligent budget control
A common approach to budgeting in metalworking operations is to acquire every element of the process at the lowest price possible. However, it is best not to base tool selection on price alone. Before discussing prices, a shop should consider the desired end results. If a tight-tolerance, top quality part is the goal, more-expensive precision tooling will be required to machine it.
Figure 2: Different selection criteria for tooling
The cost of struggling with bargain tools to achieve high part quality and producing unacceptable parts will exceed the expense of higher-priced tooling. On the other hand, when quality demands are less stringent, a portion of the capabilities of high-precision tools will be wasted. Recognising the ultimate goal of the process is the first step in cost-effective purchasing decisions.
Intelligent handling of constraints
Real-world metalworking operations, as opposed to theoretical discussions of metalworking theory, are bound by practical constraints that include machine power and stability and customer demands regarding dimensions and surface finish quality. Cutting conditions can be varied over a wide range, but the effects of different combinations of parameters on cutting forces and surface finish may limit some choices.
Figure 3: The two-step model for cutting condition selection
Nonetheless, simply reducing cutting parameters overall is not an intelligent way to deal with process constraints. For example, changes in depth of cut have a greater effect on the consumption of machine power than changes in feed rate. The combination of decreasing depths of cut and increasing feed rate can improve productivity within the constraint of limited machine power.
Tool application rationalisation
Considering the massive number of tool geometries, sizes and materials available, the possible configurations of metalcutting tools are practically endless. Machine shops typically make tool application choices one operation at a time, choosing a specific tool to create a certain feature on a part and then picking another tool to machine another different feature.
Figure 4: The total offer for tooling is enormous – rationalisation is the key
In an example case, two separate tools would be used to turn a shaft and produce a wide groove with two square shoulders. Specifically, one tool turns the shaft to the desired diameter and cuts one shoulder and the width of the groove, followed by a second tool that cuts the other shoulder. Each tool is programmed and optimised separately, representing separate programming and administrative costs.
A contrasting tool selection strategy is to develop a highly-specialised custom tool that can create multiple features in one machining pass. The strategy is convenient but the design and manufacturing of special tools is expensive.
Between the two extremes is an approach that utilises a standard tool engineered to perform more than one operation (multi-directional tooling). A perfect example of this approach is a Seco’s MDT tooling.
The tool’s features enable it to turn the diameter, plunge in to create one shoulder, move across the shaft to cut the groove, then withdraw to form the second shoulder. Even if such a multidirectional tool does not operate at the optimised cutting parameters of the two separate tools, the savings in tooling, programming, tool change time and inventory costs make the multidirectional tool the preferred choice.
Complex workpiece approach (group technology)
Comparable to the technique of applying tools that combine two or more operations, a shop can choose tools that are capable of creating similar features across a range of workpieces. A shop may machine a wide range of different workpieces, but the workpieces will share common features such as holes, slots and milled surfaces.
To expedite the machining of complex parts, a shop can view similar features as a group and choose a tool optimised for a certain operation, such as holemaking, that is repeated on different parts. The optimised tool maximises productivity and also reduces cost when considering the engineering time that goes into repetitively programming tools for each separate part. The group technology approach also helps reduce tool inventory.
Achieving minimal functional workpiece quality
Although the concept initially may seem strange, shops must realise that it is necessary to achieve only the lowest possible workpiece quality that meets customer specifications and functional requirements. There is no need to exceed those requirements. If a part tolerance is 5 microns, achieving 3 microns is a waste of time and money. Higher quality tooling and more precise operating processes will be required to achieve the tighter tolerance. But customers will refuse to pay for such unrequested higher quality, and the job will be a money-losing proposition for the shop.
Figure 5: Total quality of a finished workpiece is influenced by a big number of elements
Some quality issues, such as burrs, obviously must be resolved. And there are situations where minor cost considerations are irrelevant – tool cost differences of a few Euros or cents are meaningless when compared to the value of a large titanium aerospace component the tool will machine. To maximise cost efficiency, a shop should tailor production quality to the functional and quality requirements of the workpiece.
Predictive tool maintenance
Traditional tool maintenance is reactive. When a tool wears out or breaks, it is replaced. That approach, however, generates costs beyond those of the tool itself, including manufacturing process downtime and possible damage to the workpiece. Preventive tool maintenance is a step beyond reactive maintenance.
Figure 6: Cutting tools wear out due to different phenomena
The useful lives of even identical tools usually vary above and below an average length of time. Preventive tool maintenance is based on replacing the tool before it reaches its shortest expected working life to be sure that the change is made before the tool wears out too much or breaks. That approach, however, wastes tools with a tool life that is at or above average.
A relatively new approach, based on tool life modeling, uses computer calculation and simulation to provide predictive data on tool deterioration and to indicate when replacement is due. At a somewhat greater expense, use of sensors can further fine-tune the results by tracking tool wear in real time. Use of predictive tool maintenance has the potential to reduce tooling costs by 15 percent, 20 percent or more.
Tool inventory control
When dealing with the second – collection – phase of metalworking production, it is important to note that tool inventory control is different than tool management. Tool management refers to organising an existing tool inventory and making it available for production. For that task, a variety of automated tool management systems is available. Tool inventory control, on the other hand, is an effort to rationalise and consolidate the number of tools a shop possesses to focus on what is really needed. If tools are not rationalised before being loaded into an automated tool dispenser, the result is simply automated disarray.
Practical work analysis
In his 1907 book “On the Art of Cutting Metals” American engineer and work analysis pioneer Fredrick Winslow Taylor noted that some of the activities in a workshop, such as milling a surface, clearly add value to a workpiece. On the other hand, he noted that many activities that are necessary for the production of a finished workpiece do not directly add value. These include e.g. fixturing the workpiece on the machine or writing the machining program.
Taylor said that non-value-adding tasks should be completed as fast as possible and in a way that minimise their effects on the total costs of production. Automation can accomplish tasks such as part loading and fixturing and save time and money.
Figure 7: Productivity and cost efficiency can be achieved through different roads
Manufacturers typically believe that the best way to reduce processing time is to increase machining parameters. Most shops do not fully recognise the time consumed by activities such as engineering. A task that can represent as much as 40 percent of the total time for a part to travel from drawing to delivery. Unplanned downtime caused by tool failure, quality issues or chip control problems also may be overlooked. When analysing work activities and costs, it is essential to consider all the contributors to part production time.
Practical application of optimisation
The third phase of metalworking part production, the realization phase, puts into action the tools and strategies selected in phase one and collected in phase two. Rarely if ever does a process work exactly as planned, and it is at this point where optimisation of the operations in terms of speed, reliability and other factors is necessary. Additionally, most shops also seek to improve ongoing processes. After carrying out the organisation and rationalisation steps of phases one and two, practical optimisation enables a shop to find technical and economic benefits in a combination of feed, speed and depth of cut that produces the desired results.
Intelligent introduction of new technology
Manufacturers today face a range of relatively new challenges including mandates for sustainability and environmental protection. Intelligent introduction of new technologies and processes enables shops to fulfill the challenges. Dry machining, for example, permits a facility to reduce the use of coolants, which in turn reduces the potential effects of the fluids on the environment as well as the cost of safely disposing them. Growing use of lead-free workpiece materials is aimed at removing the harmful metals from the environment. Improving process parameters and production tooling performance will result in measureable savings in energy expenditures.
Figure 8: Developments in machining processes
Conclusion: phase 4 and STEP education
As manufacturers of any size utilise the ten simple steps to improve their operations, a fourth phase of the production process involves ongoing internal education. The goal of that education is to ensure shop personnel realize solutions to productivity issues do not always necessitate huge investments, high technology and expanded workforces.
The lessons learned while improving an operation or a family of operations can be reapplied and expanded to include similar situations throughout an entire shop. These lessons can be supplemented with organised education such as the Seco Technical Education Program (STEP), a well-developed and practical program designed to familiarise users with the latest tooling systems and techniques. Combined with practical experience in process analysis and improvement, education is the key to establishing a culture of problem-solving and process improvement that will result in ongoing manufacturing success.
Figure 9: Total STEP offer