One of the best ways to reduce quality problems is to increase cycle time.
|
The methodology utilizes best practices from software development best practices such as CMMI, Six Sigma, TQM, Lean Initiatives, and cycle time reduction and applies these notions for repeatability, consistency, automation, and error reduction. Show
DV2 methodology focuses on rapid sprint cycles (iterations) with adaptations and optimizations for repeatable data warehousing tasks. The idea of DV2 methodology is to enable the team with agile data warehousing and business intelligence best practices. DV2 encompasses methodology as a pillar or key component to achieve the next level of maturity in the data warehousing platform. Other methodologies are available for use; however, the DV2 methodology is uniquely geared to leverage the benefits of the DV2 model, process designs, and much more. Read moreNavigate DownView chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780128169162000188 Production scheduling, management and controlIn Practical E-Manufacturing and Supply Chain Management, 2004 Prioritization flowCalculation of lot priority incorporates tool limitations and variations with the four rules listed above. The RTD implementation for lot dispatching in one company continuously reduced the mean and variance of cycle time. The trend chart with weekly data is shown in Figure 9.5, illustrating a cycle time reduction of 31.3% from May 1997 to July 1998 and 52.3% reduction in cycle time deviation for the same period. In addition to cycle time reduction, the RTD simplified procedures for choosing which lot to run next. As more of the dispatching system was implemented (bars), cycle times became shorter and more consistent. The error bars represent one standard deviation in each direction.  Figure 9.5. Cycle time improvement View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780750662727500129 Engineering the Agile Supply ChainDenis R. Towill, in Agile Manufacturing: The 21st Century Competitive Strategy, 2001 4. BENEFITS OF MOVING TOWARDS THE SEAMLESS SUPPLY CHAINA major factor in enabling agile supply is the compression of total cycle time (TCT) i.e. the time taken between customer need identified and that customer need being satisfied. This is convincingly demonstrated via our Case Studies. By concentrating on TCT reduction via properly analysed and implemented re-engineering programmes, the business bottom-line is leveraged by improving all the important management metrics. This is illustrated in Fig. 1, where typical results are shown on the impact of TCT reduction on productivity indices, WIP, stockturns etc. (Thomas, 20). These results confirm the power of utilising time metrics as explicit goals in re-engineering programmes. We regard the Time Compression Paradigm as a necessary, but not sufficient condition for agility. Yusuf Sarhadi, and Gunasekaran (21) highlight this fact by emphasising that agility is just not doing things fast, but requires massive structural and infrastructure changes as clearly visible in all three of our Case Studies. Some specific publicly quoted cost benefits potentially achievable by better pipeline management and hence moving towards the SSC include: Fig. 1. The Power of Total Cycle Time Compression: Input-Output Diagram Showing Range of Business Performance Improvements (Source: Thomas, 20)•United Health Company estimate that £K50 p.a. is saved for every day by which their “total order fulfilment cycle” is reduced (Evans et al, 22). •Hewlett-Packard suggest that between 25% and 50% of total system stocks may be eliminated (even in well run chains) by strategic re-distribution of stocks (Davis, 23) •The U.K. Institute of Purchasing and Supply argue that some companies spend up to one third more than necessary by adopting the wrong purchasing policy such as price rather than total worth (Cassell, 24) •Phillips (USA) experience is that companies can save up to 10-15% of their annual revenues presently tied up in supply chains (Schmidt, 16) •Elders (New Zealand) estimate they can save $K150 transport costs by better design and management of outboard logistics (Kosta, 25) •McKinsey and Co. argue that between 10 and 40% of total supply chain costs are due to complexity much of which can be eliminated by streamlining products, processes, flows and inventories (Child, Diederichs, Sanders and Wisniowski, 24) •UK retailers could treble profit margins (which are well known to be under constant threat) by more efficient management of their supply chains (Gilchrist, 27) These actual and potential savings are impressive and importantly cover a wide range of market sectors. They provide a helpful way of influencing businesses to plan and implement change and can be seen as providing a useful adjunct to management consultants sales pressure by providing independent evidence that collaborative movement towards the SSC can provide a powerful competitive edge. However, as Womack and Jones (28) have stressed, the agreement between partners has to be “shared pain and shared gain”. This is particularly true in agile supply as the trust necessary to manage the entire chain effectively can be destroyed if strong “players” selectively grab the profits but attempt to pass on any losses to their more vulnerable brethren. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780080435671500206 Gaining Agility Through Supply Chain ManagementTareq Suleman, Mohamed Zairi, in Agile Manufacturing: The 21st Century Competitive Strategy, 2001 3.2. Inventory & Time ManagementThe second tool that has to be effectively utilised by organisations is that of inventory and time (cycle) management. Products are evolving, markets are changing and technology is advancing rapidly. The business world is changing rapidly for both customers and organisations. Customers of today are more and more demanding, they want high quality products and services – manufactured and delivered to the highest standards. Organisations, therefore, have to respond to these needs, otherwise the competition is out there – ready to pounce and lead customers away. Businesses have realised that they need to be more responsive to the needs of their customers and offer shorter cycle times in both manufacturing and delivery. In other words, become ‘lean, mean business machines’ – its not jut good enough to survive, they have to become world leaders. Supply chain mistakes, therefore, cannot be tolerated because as mentioned earlier, customers can turn way to the competition. An effective supply chain that utilises the tools of inventory and cycle management will be in a position in any situation to deliver top quality products, quickly and accurately. These companies have implemented business wide philosophies of Quick Response (QR) and flexibility into their day-to-day culture (Handfield & Nichols, 1999). Basically, Handfield and Nichols describe these companies as paying attention to time – be it lead-time reduction, time compression, QR, etc, these time based methods are an effective means by which a company can grow, make large profits and control operational problems of overheads and inventory costs. Inventory has always been a problem for many organisations, but with an integrated supply chain, inventory can decrease throughout the chain. Instead of holding large stockpiles of products – time based firms cut their costs by managing their businesses so that inventory/materials flow smoothly with little or no delay between members of the supply chain, in the required quantities, right destination, at the right time and at the required specification. 3.2.1 LogisticsAs mentioned previously in chapter two, logistics is an integral part of SCM and is associated with moving inventory (materials or goods) smoothly through a supply chain (see Fig.2.1). The definition given by the council of logistics management is – ‘Logistics is the process of planning, implementing and controlling the efficient, effective flow and storage of goods, services and related information from point of origin to point of consumption to meet the customer requirements'(Palevich, 1999). Logistics includes the following main areas: •Warehousing •Inventory Management •Transportation Engler and Natalie (1997) state that according to the US department of commerce, nearly 60% of all Fortune 500 companies logistics costs are spent on transporting products from manufacturers to distribution centres or retailers. Furthermore, transportation costs chew up 2% to 8% of a companies sales … therefore, for a multibillion dollar organisation, shaving even 1% off these costs can add up. So huge is its impact on SCM, many organisations are implementing logistics or finding new ways to enhance logistics capabilities throughout their supply chains – with world class SCM organisations such as Wal-Mart leading the way. Two major areas that are impacting on logistics are the role of IT and third-party logistics vendors. Many companies prefer to keep 100% control of their logistic processes, but evidence (Engler and Natalie, 1997) has shown that outsourcing and building partnerships with third party logistics providers is becoming more and more popular. The KPMG survey (Engler and Natalie, 1997), of 360 logistics professionals has shown that almost 40% of respondents planned to rely more heavily on third party providers in the closing year. Logistics is one area where paperwork never seems to end, from purchase orders to routes and maps. The survey by KPMG, further indicated that whilst most of the respondents believed that, IT would eventually have a major impact on logistics, only 21% said that such systems are currently well-integrated with the logistics processes within their organisations. Typical IT tools that can alleviate much of the many problems associated with logistics range from warehouse management systems and bar-coding and scanning to transport routing systems. 3.2.2. Cycle TimeAs mentioned earlier in the chapter, organisations that pay attention to time and deliver customer requirements in the right quantity, at the right time and at the right place, will gain competitive advantage over their rivals. The reduction of the time required to deliver a product to a consumer is a major cycle time problem for many businesses. Within an integrated supply chain, the overall cycle time reduction exercise, can be broken down into its components throughout the supply chain. The three parts that make up the supply chain – upstream suppliers, focal organisation and downstream distribution channels, can all look at ways to reduce their own internal cycle-times (see Fig 2.1). Areas for cycle time improvement are: ▪Planning / Forecasting Cycles ▪Procurement / Purchasing Cycle ▪Manufacturing Cycle (batching, lean manufacture, machine changeovers, …) ▪Inbound Logistics (transportation, goods in, warehousing, inspection, …) ▪Customer service (order processing, …) ▪Outbound logistics (transportation, warehousing, documentation, …) ▪Customer Service (returns, warranties, …) Much has been written about methods/techniques used to reduce cycle times within specific organisations. As (Handfield and Nichols, 1999) state, there is no one ‘right-way’ to do this, instead they propose a method based on the process-improvement approach developed by (Harrington, 1991) which is focused on cycle time performance: 1.Establish a Cycle Time Reduction Team (CTRT) - team members should represent all functions of the organisation that have a direct impact on the process being investigated. 2.Develop an understanding of the given supply chain process and current cycle time performance. CTRT teams in ‘workshops’, develop an understanding of the current process and its associated cycle time performance characteristics. 3.Once point two has been completed, identify opportunities for cycle time reduction. 4.Develop and implement recommendations for cycle time reduction. 3.2.3. Pull-Push StrategiesA major area that has a great bearing on cycle times is that of pull and push strategies. Although a pull strategy (JIT) is synonymous with SCM, push strategies cannot be discarded completely – because a pull strategy that works for one organisation might not work for another. That organisation might then decide to use a hybrid system that will be ‘fit for purpose’. (Tompkins, 1998) explains the different types of strategies very simply and accurately: Push Strategy: In a push environment, a product goes directly from the palletizer at the manufacturing facility to the distribution facilities. There's absolutely no room for storage. Product is made and shipped to the distribution centres based on forecasts of demand. The advantages of this system are: 1.There's no requirement for warehouses at the manufacturing sites 2.Customer satisfaction is high because plenty of stock is available and delivery time is short 3.Product is shipped from the factory in full truckloads, saving costs and improving scheduling and handling. However, the Push strategy has the following disadvantages: 1.Forecasts are inaccurate, safety stock is required at different points and therefore larger distribution centres 2.The larger the distribution centres are, the more safety stock is required – thus increasing costs and decreasing the ability to forecast. Pull strategy: Here a product is not shipped until something – a retail sale, for example, triggers an order for replenishment. Advantages for this system are that: There is no finished goods or manufacturing inventory 2.There is no concern about forecast accuracy because of the pull system 3.Pulling allows links in the chain to be cut, as deliveries are made direct to retailers. There are, however, two minor disadvantages to the pull system: 1.Small lots may have to be manufactured, which may cause inefficient manufacturing 2.The assumption that all customer orders can be fulfilled may not be possible for a number of reasons. Hybrid System: A system of this kind may allow an organisation to push its popular products and pull the slow movers. If a product is being made that everybody uses in quantity- the push system is used. The forecast doesn't have to be that accurate and if a stockout does occur, the organisation can always catch up. The slow moving products can be left back in a central location and pulled from that. The advantage of a hybrid system is that a smaller warehouse can be used at manufacturing and the higher volume products move in truckload quantities to the distribution centres. The advantages of a pull over a push system are: •Reduced stock transfers •Reduced safety stock •Direct customer shipments •Improved customer service View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/B9780080435671500395 Quality Software DevelopmentRini Van Solingen, David F. Rico, in Advances in Computers, 2006 3.2 Benefit Models for SPIBenefit models are simple equations, formulas, or functions that are used to measure, quantify, and estimate the economic value, profit, savings, or reward of implementing a new SPI method. SPI methods are designed and implemented in order to yield economic or monetary benefits such as increased customer satisfaction, productivity, quality, cost savings, and cycle time reduction. A long used, classical, and authoritative approach to quantifying the benefits of SPI methods is to measure total life cycle costs before and after the introduction of a new SPI method. There are seven benefit models or total life cycle cost models which are very useful for estimating the economic value of the six major SPI methods as shown in Table VII. There are benefit models for old costs, Inspections, PSPsm, TSPsm, SW-CMM®, ISO 9001, and CMMI® [67]. Table VII. Benefit Models of SPI Methods with Examples for a 4 Person Team Implementing 10,000 LOC MethodBenefit models and worked examplesHoursCostsOld CostsLOC × 10.51 − Test_Hours × 945,100h$4,509,99710,000 × 10.51 − 6,666.67 × 9InspectionsLOC × 10.51 − Inspection_Hours × 99 − Test_Hours × 917,425i$1,742,53310,000 × 10.51 − 708.33 × 99 − 1,950 × 9PSPsmLOC / 25400j$40,00010, 000/25TSPsmLOC / 5.93471,685k$168,50110,000/5.9347SW-CMM®LOC × 10.2544 − Inspection_Hours × 99 − Test_Hours × 914,869l$1,486,93310,000 × 10.2544 − 708.33 × 99 − 1,950 × 9ISO 9001LOC × 10.442656 − Test_Hours × 9 − Rework_Savings39,402m$3,940,15610,000 × 10.442656 − 6,670 × 9 − 4,995CMMI®LOC × 10.2544 − Inspection_Hours × 99 − Test_Hours × 9 14,86914,869n$1,486,93310,000 × 10.2544 − 708.33 × 99 − 1,950 × 9 Total life cycle cost is an estimate of complete software development and maintenance costs. The basic form of the total life cycle cost model is LOC × (Defect_Rate × 100 + Software_Effort/10,000) − Inspection_Hours × 99 − Test_Hours × 9. LOC refers to lines of code, Defect_Rate refers to the defect injection rate, and Software_Effort refers to analysis, design, and coding hours. Inspection_Hours and Test_Hours are self explanatory. With a Defect_Rate of 10% or 0.1 and a Software_Effort of 5,100, the basic total life cycle cost model simplifies to LOC × 10.51 − Inspection_Hours × 99 − Test_Hours × 9. This total life cycle cost model signifies complete software development and maintenance costs, less the benefits of inspections and testing. If no inspections or testing are performed, then the total life cycle cost is LOC × 10.51 or 105,100 hours for a 10,000 line of code application. If we perform 708.33 hours of inspections and 1,950 hours of testing, then the total life cycle cost is LOC × 10.51 − 708.33 × 99 − 1,950 × 9 or 17,425 hours, a savings of 87,675 hours. (This is an extensible model which can be calibrated for varying defect rates, software effort, and Inspections and testing efficiencies. Furthermore, it can be augmented to model the economics of automatic static source code analysis and analyzers.) The Old Cost benefit model represents a reliance on 6,667 testing hours to remove 667 defects, or 45,100 total life cycle hours for 10,000 lines of code. The Inspections benefit model represents a balance of 708.33 Inspections hours and 1,950 testing hours, or 17,425 total life cycle hours for 10,000 lines of code. The PSPsm and TSPsm benefit models signify a productivity of 25 and 5.9347 lines of code per hour, or 400 and 1,685 total life cycle hours for 10,000 lines of code. (The PSPsm and TSPsm benefit models don’t use the total life cycle cost model because they result in zero defects, and therefore exhibit little or no post-delivery economic activity.) The SW-CMM® benefit model results in 2,544 development hours at Level 3, 708.33 Inspections hours, and 1,950 testing hours, or 14,869 total life cycle hours for 10,000 lines of code. The ISO 9001 benefit model results in 4,426.56 development hours, 6,670 testing hours, and Rework_Savings of 4,995 hours, or 39,402 total life cycle hours for 10,000 lines of code. The CMMI® benefit model results in 2,544 development hours at Level 3, 708.33 Inspections hours, and 1,950 testing hours, or 14,869 total life cycle hours for 10,000 lines of code. View chapterPurchase book Read full chapter URL: https://www.sciencedirect.com/science/article/pii/S0065245805660019 Operational ThinkingJamshid Gharajedaghi, in Systems Thinking (Third Edition), 2011 6.3 Dynamics of throughput systemsIn a global economy, price is set by the global market, making it an uncontrollable variable. This renders Sloane's famous “cost plus” pricing policy obsolete. Sloane's famous assertion, that cost is an uncontrollable variable and price consisting of cost plus a reasonable profit is the controllable variable, led to a dominating cost plus economy in America that lasted for a long time. But the game has changed. Today, the only way to compete is to reduce cost, improve throughput by periodically redesigning the product and throughput processes, and remembering that 75% of the cost is design driven. But to improve throughput requires that we deal with the following four interdependent variables simultaneously: cycle time, cost, flexibility, and quality. This can only be done by building a dynamic model of the throughput process that is capable of dealing with interdependent variables. We have defined throughput as the process of generating and disseminating wealth. It contains all of the activities necessary to obtain required inputs, convert inputs to outputs, and then take the final products to market. Therefore, marketing, selling, order processing, purchasing, producing, shipping, billing, and accounting — in addition to cash management, quality, time, and cost — are among the activities of a throughput chain. The list of activities for a service industry might be slightly different; for example, throughput of an education system will include activities for selecting and registering students, scheduling the courses, teaching, giving exams, and issuing certifications. Meanwhile, the throughput of a health-care system may include access to patients, access to health-care providers, interface with third-party payers, delivery of health care, delivery of patient care, and management of the reimbursement system. Nevertheless, it is obvious that even a simple throughput consists of a chain of events and activities that need to be integrated. Since these activities are usually carried out by different groups in different departments of an organization, strong interface and effective coupling among them are a must for a competitive throughput. Actually, to design a throughput system, we need to •Know the state-of-the-art, as well as availability and feasibility of alternative technologies and their relevance to the emerging competitive game •Understand the flow, the interface between active elements, and how the coupling function works Appreciate the dynamics of the system such as the time cycle, buffers, delays, queues, bottlenecks, and feedback loops •Handle the interdependencies among critical variables, plus deal with open and closed loops, structural imperatives, and system constraints •Have an operational knowledge of throughput accounting including target costing and variable budgeting Figure 6.22 describes elements of a holistic approach to designing a throughput. The basic elements of this scheme are the critical properties of the process, model of the process, and the measurement and learning system. Figure 6.22. Elements of a throughput process. 6.3.1 Critical Properties of the ProcessThe most important element in our throughput scheme is identification of critical properties of the process. Time, cost, flexibility, and quality are usually among the major factors that determine the success of a throughput process. They form an interdependent set of variables so that each one can be improved at the expense of others. Treating them as independent variables, as is normally done, is an unacceptable mistake. Unfortunately, expertise is in any one of the areas of time cycle reduction, cost control or waste reduction, and quality control. Each expert tries to suboptimize the single area of her/his concerns by manipulating the process. This might lead to incompatibility among the solutions. The challenge is to reduce cycle time, while eliminating the waste and ensuring availability of the output (in kind, volume, space, and time), in addition to managing the process in such a way that it is “competent and in control” all at the same time. This can only be done by simulating the throughput process by building a dynamic model. 6.3.2 Model of the ProcessThe model of a throughput process in its simplest form is a set of interrelated activities designed to produce an explicit output. Different ways and several levels of sophistication can be used to model a process. The most common is a simple flow chart. However, to get a handle on interdependencies and the dynamics of the system, I like to use the iThink software to simulate throughput processes. In addition, I believe Eliyahu Goldratt's (1997) constraint theory or more specifically his book, Critical Chain, is a must read and a fitting complementary tool to our throughput modeling formulation. In Critical Chain, Goldratt, by recognizing principles of multidimensionality and emergent property, demonstrates beautifully why local optimization does not lead to global optimization. Using the chain as an analogy for a throughput he asserts that the strength of the chain represents the throughput of a process, and the weight of the chain represents its cost. Then he goes on to argue why we have lost the luxury of choosing between increasing the throughput or reducing the cost, why the old dichotomy is not valid anymore, and that to survive we need to increase throughput and reduce cost at the same time. Since the strength of a chain is defined by its weakest element, he proposes an iterative process of strengthening the weak links in sequence of the weakest link first. Each iteration improves the throughput to the next limit defined by the next weakest element with a minimum cost, thus eliminating the cost of over-designs. Then using his ingenious observation that time estimated to finish a task with 80% of confidence is three times greater than the most probable time it takes to finish the task (see Figure 6.23) Goldratt develops an elegant scheme that artfully uses buffers to significantly reduce time, minimize waste, and improve flexibility of a throughput process. Figure 6.23. Probability of finishing a task. Note that the area under the curve is the probability of finishing the task on time. The higher the uncertainty, the longer the tail of the distribution. Median means that there is only a 50% chance of finishing at or before this time. To reiterate our early discussions about developing a dynamic model of a throughput process, I would like to re-emphasize the point that the simplest way to build a dynamic model is to identify and map the behavior of the relevant throughput variables, the manner in which the variables change, and the way they relate to one another. Using a simplified version of the conventions and icons provided by the iThink program — stocks, flows, converters, and connectors — we can map the behavior of each variable separately and then put them all together in a web of interde-pendencies. The following example represents a real case of throughput modeling using iThink. In 1997 I received a request from a prominent telephone company for help to overcome a critical challenge in their throughput system — the inability of the existing structure to serve the rapidly expanding customer demand to meet the requirements of the Internet era. Unprecedented demand had resulted in unacceptable levels of malfunctioning of the throughput system. Consequently, customer complaints had reached such a level that the FCC had been forced to impose crippling financial penalties on the company. The four interdependent throughput activities — installation, repair, maintenance, and planned capacity expansion — were not only influenced and disturbed by rapid growth of the customer base but also with the ever-difficult task of allocating the limited and overworked technical resources to competing activities. The simulation of our iThink model (Figure 6.24) that captures the interactions among all of the previously mentioned variables pointed to these four areas of trouble: Figure 6.24. iThink model for telephone operation. 1. Slack factor: Traditionally 25% of telephone lines in a given installed cable are reserved to replace active lines in case of future failures, but unprecedented demand of the existing customers for additional lines for Internet activity had forced the company to use up the slack lines. Therefore when an active line for any reason had failed, under customer pressure, it was switched to another active line. As expected, this only bought a few days before adding another complaint to the accumulating list of existing ones. 2.Functional organizational structure: Each of one of the interrelated activities captured in the following model was the responsibility of a separate department. All of the reward systems were volume-based not result-oriented. Blame was the common game played artfully by all involved. There was a constant power struggle and fight for additional resources. 3.Increased number of hands in the plant: Competing interest among different functions had increased “hands in the plant.” This, along with poor and irresponsible documentation, undermined the “quality of the records” for each plant and increased the level of malfunctioning. There was a high correlation between the number of hands in a plant for a given period and the number of additional complaints reported. 4.Volume based reward system: Workers were also enjoying record earnings based on overtime pay and took full advantage of the volume-oriented reward system. The mess was dissolved within three months after a modular design replaced the existing structure where all interdependent activities were given to a neighborhood center with a reward system based on results and customer satisfaction instead of volume. A team of technicians was assigned to a given neighborhood and was told they would receive their full overtime pay if the number of customer complaints for a given period fell below a normal rate. Module managers were given the authority to limit the installation of new lines based on the state and quality of the plant and slack factor at the same time expansion of the plant capacity was oriented more toward the weakest link rather than the convenience of the capacity expansion group. See Chapter 7 for discussion of modular design. Finally, we do recognize that the main function of a business is to produce a throughput, that is, to generate and disseminate wealth. However, an effective throughput cannot be designed independent of organizational processes that provide the platform and infrastructure for its operation (Figure 6.25). The holistic approach requires that designers explicitly define the parameters of these subsystems and understand the behavioral implication of different designs. Figure 6.25. Throughput and organizational processes. Design parameters and characteristics of organizational processes are basically defined by assumptions and imperatives of the dominant culture or the paradigm in use for each organization. The four organizational processes are very much interdependent and value driven. Together, they define critical attributes of the organizational culture. More often than not, these attributes are produced by default rather than design. Once in place, however, they remain intact during ups and downs of technological change. Throughput processes, on the other hand, are technologically driven. They explicitly define how the output of an organization is to be produced in the context of a given technology. Uniquely designed for each output, throughput processes are subject to continuous change and improvement. Since throughputs are redesigned more frequently, there is always a good chance those new generations of throughput designs will become incompatible with more traditional organizational processes already in place. This has been the major cause of the failures, already witnessed, in most re-engineering efforts of recent times. A redesigned throughput process cannot be effectively implemented without proper concern for its compatibility with the existing order — the organizational processes already in place. Usefulness of any model, needless to say, depends on the validity of the underlying assumptions used to develop the operating formulas behind the icons. What are the methods are used to reduce cycle time?Cycle time reduction is accomplished through a variety of kaizen methods—jidoka (separating people from machines), improving manufacturing fixtures, redesigning parts to make them easier to assembly, improving software, poka yoking processes, and whatever else creative employees can think of.
What causes cycle time to increase?In order to make cycle time improvement, teams are required to optimize their current process. In most cases, you'll find that concurrent work and context switching drastically increases the total cycle time for each task.
Why is it important to reduce cycle time?Cycle time reduction benefits include faster time-to-market and, if other cost factors are kept in check, an opportunity for higher profitability. Cycle time reduction also helps a company be more competitive against other businesses that offer similar products to the same customer base.
Is one of the most common technique to reduce set up cycle time?The cycle time can be reduces of any manufacturing component by various ways. The most effective lean technique is used to reduce it. The system focused on pinpointing the major sources of waste by using tools such as JIT, setup reduction.
|
