The First Five Steps To Peak Performance And Productivity (Part One of a Two Part Series)
Fundamental principle – 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 addressed as well. To remain competitive and profitable, shops continually seek the most economical and productive ways to accomplish their work. Agreed?
Along the way, there are many influences, some unforeseen. Scientific data such as cutting conditions and machining figures are known, or at least more easily known. But, to make the most out of manufacturing economics, shops continually strive to minimize or eliminate problems like unplanned stops and scrap. But, what if we had more warning (knowledge) about the things that might go wrong? Enter technology and a better way.
The ultimate example of process improvements today are grouped into the Industrial Internet of Things (IIoT) or Industry 4.0 – strategies and tactics that integrate state-of-the-art data acquisition, storage and sharing technologies into the manufacturing process. This tech environment is currently the top level of manufacturing evolution, requiring strong management commitment, specialized personnel and significant investment.
Still though, and unfortunately, many shops lack the extensive resources of global industrial giants – such as General Electric or General Motors – and are feeling that productivity improvements are out of reach. This is not the case. Simple, cost-effective analyses and actions are within grasp, and 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 organize current equipment and practices. Interested?
THREE PHASES AND THE FIRST FIVE 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. Realization is the third phase and puts the process into action.
In many 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. Let’s begin with the first five.
1. 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.
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. Recognizing the ultimate goal of the process is the first step in cost-effective purchasing decisions.
2. 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.
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.
3. TOOL APPLICATION RATIONALIZATION
Considering the massive number of tool geometries, sizes and materials available, the possible configurations of metal cutting 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.
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-specialized 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 utilizes 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 optimized 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.
4. 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 optimized for a certain operation, such as holemaking, that is repeated on different parts. The optimized tool maximizes 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.
5. ACHIEVING MINIMAL FUNCTIONAL WORKPIECE QUALITY
Although the concept initially may seem strange, shops must realize 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 un-requested higher quality, and the job will be a money-losing proposition for the shop.
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 maximize cost efficiency, a shop should tailor production quality to the functional and quality requirements of the workpiece.
In part two we’ll cover the next five key steps to peak performance and you can find it here.