Quality And Productivity

 Quality and Productivity

 

The Quality and Productivity work group focused on requirements to maintain and improve the quality of forged parts and decrease dimensional variation among parts, while increasing all-around productivity. Group members included representatives from forging companies, forging equipment suppliers, steel manufacturers/suppliers, a forging industry consulting engineering firm, a DOE national laboratory, a collaborative manufacturing research and development consortium, a non-profit research organization, the Forging Industry Association, and a DOE research program. This broad mix of participants provided a good range of perspectives on the challenges and opportunities facing the forging industry in quality and productivity.

 

 

The ability of forgers to handle small orders, ensure on-time delivery, and maintain parts-per-million quality levels at low selling prices will be increasingly important in successfully competing with alternative domestic processes and off-shore competitors. The forging industry of the future will need to develop and implement a variety of advanced technologies to stay ahead of competitors on quality and productivity.

 

Strategic Targets

 

The industry's vision, Forging Industry Vision of the Future, relays a number of strategic targets for the industry to work towards over the next twenty years. The vision's targets for quality and productivity, shown in Exhibit 5-1, were the work group's initial subject of discussion. During the course of the discussion, the group agreed to a number of revisions that modify or expand the targets as outlined in the vision.

 

The first quality goal should be clarified by noting that the objective is to reduce to 25 ppm the rejected or returned work from the end-user (rather than during the entire manufacturing process). With this clarification, the 25 ppm target is a realistic long-term goal.

 

 

The ability of the industry to achieve a ±8 sigma process control level was the subject of extended discussion. There was some concern that setting this level as an industry-wide standard might be asking for higher levels of quality (which comes at a cost) than the customer really needs or wants. Cost-benefit analyses could help to determine the appropriate level of quality to strive for in different applications. Parts that will be used in very demanding applications, such as in airplanes, will require zero defects. Other parts used in less critical applications may compete more on the basis of cost than premium quality. A couple of participants noted that from the perspective of the metal suppliers, it would be very helpful to know what the end-use of the metal work piece will be so that they can properly process and test the work piece before it is shipped to the forgers.

 

Finally, the group added a third strategic target for quality improvements: No in-service failures. This target is needed to emphasize the fact that the ultimate goal of quality control is to assure that all parts perform without failure for the duration of their expected lifetime. Initially, the target was limited to eliminating in-service failures due only to problems originating from the forging process. However, since the forging company will be liable for the problem no matter where the defect originated (design, metal workpiece, etc.), the target was revised to read as above.

 

The group also modified the strategic targets for productivity that were elaborated in the forging vision. In order to make the first productivity target more clear, it was recommended that it include tons of product produced per employee. A baseline level is needed in order to measure progress, and this baseline will be particular to the forging company and product line. The second target was rewritten as "reduce per-piece manufacturing costs by 60%" to reflect the fact that labor costs are only one component of the total manufacturing cost. Lastly, the group felt that a clear definition of "up-time" was required to clarify the third productivity target. Using a definition of "scheduled" up-time (which excludes scheduled down-time for routine, preventative maintenance), the group agreed that a target of greater than 95% is necessary and achievable. Thus, the third target should be revised to read "achieve forging facility scheduled up-times of greater than 95%." This means that the forging facilities must be available and ready for work greater than 95% of the time they are scheduled to be available.

 

Technology Barriers

 

There are a number of technical problems that prevent the forging industry from achieving these quality and productivity targets today. As shown in Exhibit 5-2, these barriers are related to equipment limitations, lack of integration/communication among the different members of the manufacturing supply chain, availability of process modeling/simulation and process monitoring/control technologies, and infrastructural issues. The most critical problem area is the lack of robust, reliable, cost-effective process monitoring and control technologies for the forging industry. Without these technologies, it will be impossible to achieve the manufacturing efficiencies required to meet the industry's productivity goals and reduce the process variations that create defective or off-quality parts. One of the key problems highlighted in this category is the lack of cost-effective, robust, self-tuning sensors. Going on the premise that you cannot control what you cannot sense, a variety of sensors are needed to monitor and regulate all stages of the forging operation. Existing sensors, when available, often cannot withstand the high temperatures and force of the forging environments for extended periods. Those that can are often rendered unreliable before long because they are not capable of periodically re-calibrating themselves. Cost is also an issue, since sensors are needed for virtually all processes.

 

Exhibit 5-2. Major Technology Barriers to Achieving

Industry Targets in Quality and Productivity

( = Most Critical Problem Areas/Barriers)

Process Monitoring and Control Process Modeling and Simulation Supply Chain Equipment Limitations Infrastructure
Lack of cost effective robust, self-tuning sensors

- you cannot control what you cannot sense

Lack of computer controlled forging equipment with feedback

Lack of ways to measure dimensions of hot objects

Process capabilities not sufficient to achieve quality goals

Die material and/or lubrication limitations

Inability to make dies reproducible

Lack of technologies to test materials going to forgers

Inability to reduce variation from raw material to finished product

- microstructure

- dimensions

Too much trial and error -- not enough wide-spread, pc-based simulation tools

Inability to make a good part the first time

Emerging material properties are not well-understood

Lack of reliable, predictive simulation capabilities for the shop floor

Lack of good materials property databases and modeling capabilities

Lack of understanding as to why specs are tighter (to achieve what?)

- especially for the automotive market (not as much of an issue in aerospace)

Lack of standardized materials -- alloys

Lack of integration among materials, designers, forgers and OEM's

Poor communication on testing requirements among materials suppliers, forgers, customers

Lack of integrated product and process design

Equipment not capable of producing within limits

- lack of attention to asset maintenance -- equipment and people

Problems with repeatability and reliability with hammer equipment due to process and operator variations

Problems with heating methods and equipment

Lack of equipment optimized for forging industry

Capital inadequate to develop new process control technologies

Inadequate R&D budgets

Lack of trained personnel

Inadequate cost/ benefit analyses

Computer controls cannot talk to each other

- vendor provides solutions

Lack of interest in forging industry in K-12, vocational programs, and universities

 

Another key problem is the lack of computer-controlled forging equipment with feedback loops to detect/prevent production problems. Too often, problems are not detected until later in the process, when the cost of scrapping the product is higher. Another problem is that metal suppliers to the forging industry lack the technology required to properly, and cost-effectively, test the quality of the raw materials supplied to forgers as work pieces. A related supply chain problem is that there is a lack of communication on testing requirements and protocols among materials suppliers, forgers, and customers. Unless the metal supplier knows what the end-product will be used for and the environment that that product will be placed in, it is impossible to determine what tests should be specified. In general, a key barrier to quality and productivity goals is the lack of integration of the needs and expectations of materials suppliers, designers, forgers, and original equipment manufacturers.

 

In the category of process modeling and simulation, the biggest problem is that there is too much trial and error involved in developing the dies and processes for producing forged parts, which results in significant inefficiencies. The industry lacks validated, widely-available, pc-based simulation tools. Easy-to-use, reliable, predictive simulation tools are especially needed on the shop floor. The lack of good simulation tools leads to other problems, like the inability to manufacture the part correctly the first time it is tried. An underlying problem is the lack of good data and databases on materials properties, especially new materials, that feed into the simulation tools.

 

Much of the forging equipment available today has not been optimized for use by the forging industry, so equipment limitation problems are not surprising. The current technology is simply not capable of producing forgings that meet the long-term quality and productivity targets. Hammer technologies are a particular problem, with significant operational variations. Improvements are also needed in heating methods and equipment.

 

The final area of technology barriers, infrastructure issues, focuses mainly on problems related to education and capital. Currently, there are far too few students interested in pursuing careers in metallurgy or forging. The image of the forging industry, and most of the other "smokestack industries," is negative or non-existent among students. Without a technically skilled and educated workforce in the future, the forging industry will not be able to achieve its quality and productivity goals. The lack of capital is another main problem. The forging industry is primarily made up of small and medium-sized firms that lack the capital to invest in new technologies, test or demonstrate emerging technologies, and perform or fund research and development.

 

Research Needs

 

A wide range of research is required to overcome the technical barriers to achieving quality and productivity goals in the forging industry, as pictured in Exhibit 5-3. If started today, some of the research would be able to yield commercial results fairly quickly, within 3 years. Other research needs tackle more complex problems and would take longer to produce commercial results -- in the mid-term (3- to 10-year) time frame. A few long-term research needs to develop radically new forging equipment and processes would not be expected to yield commercially-applicable results for 10 years or more.

 

Many of the research needs are ongoing, and would be expected to produce commercial results in all time periods. The majority of these research needs require funding support from the government in order to be accomplished in the time frames described here. Since the forging industry lacks the resources to perform much R&D on its own, some of the research needs would probably be left undone and most would be substantially delayed if the government or outside support is not available. Research needs were identified for each of the categories of barriers described above and for an additional materials category. The priority research needs in each of the categories are described below.

 

Process Monitoring and Control

 

Not surprisingly, the largest number of research needs fell into this area, which was identified as the most critical problem area. Many of the research needs described here and in the category of process modeling and simulation are ultimately directed towards the development of "smart presses" that produce net- and near-net-shape forgings using advanced instrumentation, automation, and robotics. In this regard, a high-priority research need that can be accomplished in the near term is the development of hot dimensional measuring capabilities for taking real-time measurements of forgings during the deformation process. Another near-term need is for the development of vibratory signature analysis equipment that is especially designed for use by the forging industry. More sophisticated machine controls and process simulation software that can be run on a personal computer platform and are easy to use are likely be developed in the near term by individual companies for use with their particular array of equipment and product lines.

 

Exhibit 5-3. Quality and Productivity Research Needs
( = Top Priority; = High Priority; = Medium Priority)
(I = Proprietary/Company, I/I = Industry Collaboration, G/I = Government/Industry)
Time Frame Process Monitoring and Control Process Modeling and Simulation Supply Chain Equipment Limitations Materials Infrastructure
Develop real-time, hot-dimensional measuring capabilities

G/I

Develop PC-based machine controllers

I/I

Develop vibratory signature analysis equipment for forging industry

G/I

Develop more sophisticated, yet user-friendly, machine controls

I/I

Develop methods to continuously conduct real-time furnace uniformity tests

G/I

Increase government support for advanced process monitoring and control measuring equipment with cross-industry applications

G/I

- e.g., temperature measurement, dimensional measurement

Develop user-friendly interfaces for simulation software

I/I

- GUI

- touch-screen

Develop 3-D simulation technology for deformation process

G/I

Create standardized format for exchanging data on all forging processes

- STEP/ PDES

  Develop and implement technology to internally inspect the ingot

G/I

Conduct a nationwide program to interest students in the forging and basic manufacturing industries

G/I

- get forging-related courses into curriculum

- develop training modules (on-the-job)

Develop benchmarks for forging processes (open-die, etc.)

I/I

Establish a dedicated R&D center to address technical needs

G/I

- guided by industry

- "virtual center"

Develop forging industry cost models to determine value of investment

G/I

- algorithms to look at long-term value of technology investment

Develop predictive maintenance technologies specifically for forging equipment

Develop advanced sensors to measure high-temperatures, vibration, acoustics, and strain

G/I

Develop intelligent agent control technology

G/I

Develop closed-loop process controls for hot forging (requires sensors)

G/I

Develop techniques for rapid prototyping with engineering properties

- e.g., to mimic end-use product

G/I

Develop technologies to integrate process and design (computer)

G/I

Develop improved billet coatings to improve oxidation resistance

G/I

Eliminate graphite in warm forming operations

G/I

Develop quicker heating methods for bigger ingots

G/I

Perform industry-specific fatigue analysis

G/I

- parts

- products

 
Direct more research towards identifying forging processes that achieve expected product properties

G/I

- crosscutting with other categories

    Conduct research to develop new types of forging equipment

G/I

- break-throughs

- e.g., hydro-forming, zero-gravity

   
  Perform research to relate materials properties to simulations

G/I

Develop feature-based design software for forging

G/I

Determine material properties as a function of temperature

G/I

- at research center

Develop next-generation die manufacturing technology

G/I

Investigate the roles of lubricants and improve their properties

G/I

Determine existing equipment capabilities and pursue development of more preferred equipment

G/I

Generate real materials property data

G/I

Establish government-sponsored support technology interaction groups

G/I

Establish an industry-directed consortium to issue calls for proposals (e.g., Cast Metals Coalition)

G/I