Just In Time

Just In Time
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See just-in-time compilation for the technique for improving the performance of interpreted programs in computing.
Just In Time (JIT) is an inventory strategy implemented to improve the return on investment of a business by reducing in-process inventory and its associated costs. The process is driven by a series of signals, or Kanban (Jp. カンバン also 看板), that tell production processes to make the next part. Kanban are usually simple visual signals, such as the presence or absence of a part on a shelf. JIT can lead to dramatic improvements in a manufacturing organization's return on investment, quality, and efficiency when implemented correctly.
New stock is ordered when stock reaches the re-order level. This saves warehouse space and costs. However, one drawback of the JIT system is that the re-order level is determined by historical demand. If demand rises above the historical average planning duration demand, the firm could deplete inventory and cause customer service issues. To meet a 95% service rate a firm must carry about 2 standard deviations of demand in safety stock. Forecasted shifts in demand should be planned for around the Kanban until trends can be established to reset the appropriate Kanban level. In recent years manufacturers have touted a trailing 13 week average is a better predictor than most forecastors could provide.
Contents[hide]
1 History
2 Effects
3 Problems
3.1 Within a JIT System
3.2 Within a raw material stream
3.3 Oil
4 Theory
5 See also
6 References
7 External links
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History
The technique was first used by the Ford Motor Company as described explicitly by Henry Ford's My Life and Work (1922): "We have found in buying materials that it is not worth while to buy for other than immediate needs. We buy only enough to fit into the plan of production, taking into consideration the state of transportation at the time. If transportation were perfect and an even flow of materials could be assured, it would not be necessary to carry any stock whatsoever. The carloads of raw materials would arrive on schedule and in the planned order and amounts, and go from the railway cars into production. That would save a great deal of money, for it would give a very rapid turnover and thus decrease the amount of money tied up in materials. With bad transportation one has to carry larger stocks." This statement also describes the concept of "dock to factory floor" in which incoming materials are not even stored or warehoused before going into production. This paragraph also shows the need for an effective freight management system (FMS) and Ford's Today and Tomorrow (1926) describes one.
The technique was subsequently adopted and publicised by Toyota Motor Corporation of Japan as part of its Toyota Production System (TPS).
Japanese corporations cannot afford large amounts of land to warehouse finished products and parts. Before the 1950s, this was thought to be a disadvantage because it reduced the economic lot size. (An economic lot size is the number of identical products that should be produced, given the cost of changing the production process over to another product.) The undesirable result was poor return on investment for a factory.
The chief engineer at Toyota in the 1950s, Taiichi Ohno examined accounting assumptions and realized that another method was possible. The factory could be made more flexible, reducing the overhead costs of retooling and reducing the economic lot size to the available warehouse space.
Over a period of several years, Toyota engineers redesigned car models for commonality of tooling for such production processes as paint-spraying and welding. Toyota was one of the first to apply flexible robotic systems for these tasks. Some of the changes were as simple as standardizing the hole sizes used to hang parts on hooks. The number and types of fasteners were reduced in order to standardize assembly steps and tools. In some cases, identical subassemblies could be used in several models.
Toyota engineers then determined that the remaining critical bottleneck in the retooling process was the time required to change the stamping dies used for body parts. These were adjusted by hand, using crowbars and wrenches. It sometimes took as long as several days to install a large (multiton) die set and adjust it for acceptable quality. Further, these were usually installed one at a time by a team of experts, so that the line was down for several weeks.
Toyota implemented a strategy called Single Minute Exchange of Die (SMED), developed by Shigeo Shingo. With very simple fixtures, measurements were substituted for adjustments. Almost immediately, die change times fell to about half an hour. At the same time, quality of the stampings became controlled by a written recipe, reducing the skill required for the change. Analysis showed that the remaining time was used to search for hand tools and move dies. Procedural changes (such as moving the new die in place with the line in operation) and dedicated tool-racks reduced the die-change times to as little as 40 seconds. Dies were changed in a ripple through the factory as a new product began flowing.
After SMED, economic lot sizes fell to as little as one vehicle in some Toyota plants.
Carrying the process into parts-storage made it possible to store as little as one part in each assembly station. When a part disappeared, that was used as a signal to produce or order a replacement.
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Effects
Some of the results were unexpected. A huge amount of cash appeared, apparently from nowhere, as in-process inventory was built out and sold. This by itself generated tremendous enthusiasm in upper management.
Another surprising effect was that the response time of the factory fell to about a day. This improved customer satisfaction by providing vehicles usually within a day or two of the minimum economic shipping delay.
Also, many vehicles began to be built to order, completely eliminating any risk that they would not be sold. This dramatically improved the company's return on equity by eliminating a major source of risk.
Since assemblers no longer had a choice of which part to use, every part had to fit perfectly. The result was a severe quality assurance crisis, and a dramatic improvement in product quality. Eventually, Toyota redesigned every part of its vehicles to eliminate or widen tolerances, while simultaneously implementing careful statistical controls. (See Total Quality Management). Toyota had to test and train suppliers of parts in order to assure quality and delivery. In some cases, the company eliminated multiple suppliers.
When a process problem or bad parts surfaced on the production line, the entire production line had to be slowed or even stopped. No inventory meant that a line could not operate from in-process inventory while a production problem was fixed. Many people in Toyota confidently predicted that the initiative would be abandoned for this reason. In the first week, line stops occurred almost hourly. But by the end of the first month, the rate had fallen to a few line stops per day. After six months, line stops had so little economic effect that Toyota installed an overhead pull-line, similar to a bus bell-pull, that permitted any worker on the production line to order a line stop for a process or quality problem. Even with this, line stops fell to a few per week.
The result was a factory that became the envy of the industrialized world, and has since been widely emulated.
The Just in Time philosophy was also applied to other segments of the supply chain in several types of industries. In the commercial sector, it meant eliminating one or all of the warehouses in the link between a factory and a retail establishment.
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Problems
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Within a JIT System
The major problem with Just In Time operation is that it leaves the supplier and downstream consumers open to supply shocks. In part, this was seen as a feature rather than a bug by Ohno, who used the analogy of lowering the level of a river in order to expose the rocks to explain how removing inventory showed where flow of production was interrupted. Once the barriers were exposed, they could be removed; since one of the main barriers was rework, lowering inventory forced each shop to improve its own quality or cause a holdup in the next downstream area. Just In Time is a means to improving performance of the system, not an end.
With shipments coming in sometimes several times per day, Toyota is especially susceptible to an interruption in the flow. For that reason, Toyota is careful to use two suppliers for most assemblies. As noted in Liker (2003), there was an exception to this rule that put the entire company at risk by the 1997 Aisin fire. However, since Toyota also makes a point of maintaining high quality relations with its entire supplier network, several suppliers immediately took up production of the Aisin-built parts by using existing capability and documentation. Thus, a strong, long-term relationship with a few suppliers is preferred to short-term, price-based relationships with competing suppliers.
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Within a raw material stream
As noted by Liker (2003) and Womack and Jones (2003), it would ultimately be desirable to introduce flow and JIT all the way back through the supply stream. However, none of them followed this logically all the way back through the processes to the raw materials. With present technology, for example, an ear of corn cannot be grown and delivered to order [[1]]. The same is true of most raw materials, which must be discovered and/or grown through natural processes that require time and must account for natural variability in weather and discovery.
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Oil
It has been frequently charged that the oil industry has been influenced by JIT (see here (2004), here (1996), and here (1996)). The argument is presented as follows:
The number of refineries in the United States has fallen from 279 in 1975 to 205 in 1990 and further to 149 in 2004. As a result, the industry is susceptible to supply shocks, which cause spikes in prices and subsequently reduction in domestic manufacturing output. The effects of hurricanes Katrina and Rita are given as an example: in 2005, Katrina caused the shutdown of 9 refineries in Louisiana and 6 more in Mississipi, and a large number of oil production and transfer facilities, resulting in the loss of 20% of the US domestic refinery output. Rita subsequently shut down refineries in Texas, further reducing output. The GDP figures for the third and fourth quarters showed a slowdown from 3.5% to 1.2% growth. Similar arguments were made in earlier crises.
However, JIT students and even oil & gas industry analysts question whether JIT as it has been developed by Ohno, Goldratt, and others is used by the petroleum industry. Companies routinely shut down facilities for reasons other than the application of JIT. One of those reasons may be economic rationalization: when the benefits of operating no longer outweigh the costs, including opportunity costs, the plant may be economically inefficient. JIT has never subscribed to such considerations directly; following Waddel and Bodek (2005), this ROI-based thinking conforms more to Brown-style accounting and Sloan management. Further, and more significantly, JIT calls for a reduction in inventory capacity, not production capacity. From 1975 to 1990 to 2005, the annual average stocks of gasoline have fallen by only 8.5% from 228,331 to 222,903 bbls to 208,986 (Energy information Administration data). Stocks fluctuate seasonally by as much as 20,000 bbls. During the 2005 hurricane season, stocks never fell below 194,000 thousand bbls, while the low for the period 1990 to 2006 was 187,017 thousand bbls in 1997. This shows that while industry storage capacity has decreased in the last 30 years, it hasn't been decimated as JIT practitioners would prefer.
On the other hand, the storage capacity as a fraction of the daily use has decreased. American consumption has increased fairly steadily during the same period that the storage capacity has been slightly diminished. In 1975, there were approximately 20 days of storage (stocks divided by domestic production); in 1990, 14 days; in 2005, 11.5 days. When expressed as a fraction - or as the number of days' use - it has declined. This is an industry-wide phenomenon, however, and not part of a corporate plan to reduce inventory as JIT would require.
Domestic gasoline production capacity has been increased since 1975 from 14,961 thousand bbls per day to 15,572 in 1990, and 16,894 in 2005 (EIA data). In addition to the crude that is imported for production of oil, refined gasoline importation has increased from 200 thousand bbls/day in 1982 to 1,110 thousand bbls per day in 2006, or about 6% of the total. Most of that oil is imported through the Eastern Petroleum Administration for Defense district (PADD), not the Gulf Coast. Thus, the domestic gasoline production capacity has not only increased from 1975, but the total import and domestic capacity has increased while the natural variation risk has been distributed (at an increased exposure to political risk for the imported fuels).
During the same period, natural gas and airline transportation were deregulated by the 1978 Natural Gas Policy Act and Airline Deregulation Act. The former led to a gradual shift away from fuel oil toward the use of natural gas for heating and a corresponding drop in fuel oil stocks from 92,000 thousand bbls to 37,000 thousand bbls, with most of that drop coming in 1979-1986 (to 46,000 thousand bbls). The latter led to an increased refinery output of kerosene (jet fuel) as a result. From 1982 to 1990, jet fuel production increased from 753 thousand bbls per day to 1,311 thousand bbls per day, and then to 1,557 thousand bbls per day in 1999, where it peaked as a result of the subsequent economic slowdown. It currently stands at 1,538 thousand bbls per day average over the past year. Thus, gasoline production has increased at the same time as jet fuel production with fewer refineries. This is an increase in effective production capacity, not a decrease.
Other questions would have to be addressed in order to determine whether price fluctuations are due to adoption of Just In Time, other industry practices, or external factors:
Has the increase in Gulf of Mexico and Latin American oil production been the dominant reason for concentration of refinery and storage facilities in the Gulf Coast PAD district?
Have the reductions in numbers of refineries been actual shut-downs of plants, or consolidations of multiple plants under consolidated management? Have some refineries been shut down because they used outdated technology?
What effect has environmental regulation had on the industry? Specifically, what effects did the multitude of oxygenation requirements introduced in 1989-1992 have on the industry? The EPA was given broad powers to change oxygenation requirements for so-called boutique fuels, making it extremely risky for refiners to keep potentially non-compliant "finished" gasoline in stock. A sudden change in requirements could render that stock worthless, so refiners have opted instead to keep blending components on hand and improve refinery throughput.
What are the conditions of worldwide markets, i.e. is Asian demand rising? Were the markets in a state of contango or backwardation? For example, gasoline stocks were lowest during the 1997 period, probably because the price of oil fell so low that nobody wanted to store product while prices were falling.
Finally, as shown in a pair of articles in the Oil & Gas Journal, JIT does not seem to have been a goal of the industry. In Waguespack and Cantor (1996), the authors point out that JIT would require a significant change in the supplier/refiner relationship, but the changes in inventories in the oil industry exhibit none of those tendencies. Specifically, the relationships remain cost-driven among many competing suppliers rather than quality-based among a select few long-term relationships. They find that a large part of the shift came about because of the availability of short-haul crudes from Latin America. In the follow-up editorial, the Oil & Gas Journal claimed that "casually adopting popular business terminology that doesn't apply" had provided a "rhetorical bogey" to industry critics. Confessing that they had been as guilty as other media sources, they confirmed that "It also happens not to be accurate."
The automobile industry is arguably more concentrated than the oil industry, though both are clearly engaged in strong competition. Yet, only one or two automobile manufacturers are actually practicing or attempting to practice JIT, while the others have made starts toward it and then abandoned the quest. It seems unlikely, therefore, that the entire oil industry could have adopted JIT principles in unison in the 1970s and followed through until 2006.
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Theory
Consider a (highly) simplified mathematical model of the ordering process.
Let:
K = the incremental cost of placing an order
kc = the annual cost of carrying one unit of inventory
D = annual demand in units
Q = optimal order size in units
TC = total cost over the year
We want to know Q.
We assume that demand is constant and that the company runs down the stock to zero and then places an order, which arrives instantly. Hence the average stock held (the average of zero and Q, assuming constant usage) is Q / 2. Also, the annual number of orders placed is D / Q.
TC consists of two components. The first is the cost of carrying inventory, which is given by Q * kc / 2, i.e. the average inventory times the carrying cost per unit. The second cost is the cost of placing orders, given by D * K / Q, the annual number of orders, D / Q. times the cost per order, K.
Thus total annual cost is
.
We differentiate TC with respect to Q and set it equal to 0 to find the Q for minimum total cost, giving
which is known as the Economic Order Quantity or EOQ formula.
The key Japanese breakthrough was to reduce K to a very low level and to resupply frequently instead of holding excess stocks. In practice JIT works well for many businesses, but it is not appropriate if K is not small. The theory above can be fairly easily adapted to take into account realistic features such as delays in delivery times and fluctuations in demand. Both of these are usually modelled by normal distributions. The delay in delivery, in particular, means that additional 'safety stocks' need to be held if a stockout is to be rendered very unlikely.
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See also
Business
Lean manufacturing
Logistics
Management
Manufacturing
Statistical process control
Total Quality Management
Vendor Managed Inventory
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References
Editorial, "The Inventory Land Mine", Oil & Gas Journal, Vol 94, Number 29, 15 July 1996.
Goldratt, Eliyahu M. and Fox, Robert E. (1986), The Race, North River Press, ISBN 0884270629
Liker, Jeffrey (2003), The Toyota Way: 14 Management Principles from the World's Greatest Manufacturer, First edition, McGraw-Hill, ISBN 0071392319.
Ohno, Taiichi (1988), Toyota Production System: Beyond Large-Scale Production, Productivity Press, ISBN 0915299143
Wadell, William, and Bodek, Norman (2005), The Rebirth of American Industry, PCS Press, ISBN 0971243638
Waguespack, Kevin, and Cantor, Bryan (1996), "Oil inventories should be based on margins, supply reliability", Oil & Gas Journal, Vol 94, Number 28, 8 July 1996.
Womack, James P. and Jones, Daniel T. (2003), Lean Thinking: Banish Waste and Create Wealth in Your Corporation, Revised and Updated, HarperBusiness, ISBN 0743249275.
Womack, James P., Jones, Daniel T., and Roos, Daniel (1991), The Machine That Changed the World: The Story of Lean Production, HarperBusiness, 2003, ISBN 0060974176.
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External links
“NWLEAN: http://www.nwlean.net/” - The Northwest Lean Networks - A free knowledge-sharing website, with over 10,000 professionals discussing the various aspects of lean implementation.
Strengths & Weaknesses of Just In Time
“Just In Time drives on” - The Manufacturer Magazine US - An article discussing the continued impact of Just In Time in the automotive sector
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