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 Dynamisis partners work in a variety of industries, using our dynamic analysis approach to reduce costs, increase output, facilitate change and transfer knowledge. The following cases are examples of our methods and the benefits our clients realize. Production Flow - Examples from Multinationals
Production Flow - Examples from Multinationals CASE 1 - New Facility Design in the Dairy Industry The Challenge: An international dairy group wanted a standard plant design capable of processing 1.5 million liters of raw milk daily. The need to handle different types of milk, allocate equipment to different product types and meet cleaning cycle requirements raised substantially the complexity of the design brief. A worldwide firm of planning experts in the food and milk processing industry was engaged to provide the overall design. The project team recognized quickly that classic capacity design techniques based on averages could not guarantee that the facility would meet production schedules reliably and efficiently. A Dynamisis team partner was engaged to create a dynamic model that would support the design effort AND help the customer verify that the new plan would achieve the required throughput. The resulting model was completed in three months and was comprehensive in that it included flow schemes from each department and details down to the level of utility inputs, such as water and power usage. System control logic was incorporated and verified. Static schedules based on delivery deadlines and production rules were then tested in dynamic scenarios to highlight capacity restrictions. Filling equipment received special attention, because of the high capital investment required. Dynamic models clearly demonstrated optimal balance using the minimum number of pasteurizers, coolers, mixers and filling lines. The client team saw which products processed in which tanks, explored the possibilities of continuous versus batch production, and experimented with alternative approaches, such as filling and emptying a tank at the same time. Also tested was the sensitivity of the design plan to changes in product demand or product mix. The Bottom Line: Client team members were comfortable
that the new production facility would respond to their department requirements
and were confident that the design would meet capacity requirements under
a variety of scenarios. The first plant constructed using the new design
confirmed their perceptions and delivered the predicted results. CASE 2 - Material Flow in Consumer Goods The Challenge: Introduction of a new-generation product presented a leading global consumer goods manufacturer with the need for a complete redesign of the in-plant logistics of its production facility in Central Europe. A move to continuous production would require uninterrupted flow of raw materials and other inputs, but the task was complicated by the need to work within a historic facility that had process elements distributed over several floors. Extensive price competition made the need for maximum machine efficiency and minimum work-in-process important requirements for achieving the lowest possible unit costs. The American corporate parent commissioned a well-respected German logistics planning firm and specified that dynamic models would be a requirement to validate the proposed design. A complete solution was expected to incorporate material and information flows, equipment use, an AGV system, the conveyor network, goods receipt and issue. Daily handling of 6,000 containers and 1,500 pallets was also included. A key initial objective was identification of material flow bottlenecks based on anticipated allocation of plant resources. The degree of process complexity made the use of spreadsheet-based analysis insufficient, and the dynamic models quickly showed that some of the static predictions were wrong. One of the most powerful uses of the Dynamisis approach involved the creation and application of a scenario generator that could automatically create and test a variety of demand and contingency combinations. Storage and buffer areas could be dimensioned according to need. AGV and conveyor system performance were also subjected to "what..if" analysis. The results of these simulation studies were incorporated into the design and implementation of the material flow system on an ongoing basis, including hardware specifications and fine tuning of the control logic at key decision points. Ability to consider dynamic interdependencies and visualize complex flows was essential. The Bottom Line: The client found dynamic analysis
to be a cost-effective method for ensuring that capital investments were
both necessary and sufficient to meet expected output requirements and
other performance indicators. Planning became at the same time more comprehensive
and in-depth, yet the overall project timeline was shortened. The dynamic
models are now used on a continuing basis by the client to evaluate ideas
for ongoing improvement. CASE 3 - Walkers Snack Foods The Challenge: A successful marketing campaign leading to a larger share of the growing UK snack market created for Walkers, a PepsiCo subsidiary, the need to upgrade and expand its production and distribution facilities. One of the key elements in this program is the massive expansion of the factory and warehousing complex in Leicester. Added storage space was to be leveraged through operational process improvements in picking efficiency and throughput, enabling the output capacity of the complex to keep pace with expected future requirements. The Leicester complex consisted of two factories with seven production lines automatically feeding the warehouse, which was in turn connected to a regional distribution center by a monorail system that transported both full pallets and cases to marshalling lanes. Insufficient storage space led Walkers to store some products in off-site facilities. At 200 pallets/hour, distribution throughput was also inadequate to meet demand. Walkers engaged warehouse solution provider Swisslog for the design and implementation of a second, larger high bay warehouse to be fully integrated with the existing facilities. This integration would be achieved by building the new warehouse on the opposite side of the distribution center, then expanding the monorail system to serve both warehouses. The new facility would be directly linked to the factories and would use the existing picking and dispatch operations to deliver a combined throughput of 320 pallets/hour. John Coates, project director explained, "We knew that we would get some important improvements by introducing a new warehouse on the site, and so reducing the need for outside storage, which was costly and inefficient. We also believed that the existing facilities, and in particular the monorail system, had latent distribution capacity that could be utilized to cost effectively deliver a major increase in combined throughput." Though the principle was sound and management approved
the investment, this concept was based on a number of system assumptions
that needed validation before detailed design and installation began.
As Coates adds, "Significant questions remained as to whether the
monorail would simply become too easily grid-locked in practice, when
being fed from both sides, and what changes or additions would be needed
in equipment, infrastructure, and operational practices to deliver the
required throughput of goods." A dynamic model showed that the system could be used as anticipated without any major configuration changes, but it also provided important data for the overall project that would otherwise have been found only by expensive trial and error. For example, up to six additional monorail trolleys had been planned to meet the throughput requirement, but simulations proved that the existing number could meet peak demand. The result was a direct savings of £150,000. Models also showed the need for extra lifts dedicated to moving pallets from the monorail to the marshalling areas and highlighted the importance of a section of track across the centre of the circuit that acted as a quick return shortcut for emptied trolleys. The dynamic modeling approach also helped to investigate
a number of operational issues. Experimentation with the mix of products
and their allocation to the two warehouses showed that grouping high turnover
products would result in localized bottlenecks and poor throughput. Picking
rules were tested, which in turn influenced pallet storage decisions.
Swisslog project manager, Geraint Foulkes, stated: Walkers also recognized that the model could have other
potential uses and asked for the level of detail to be increased down
to the individual SKU. This effort facilitated design verification and
helped to determine optimal equipment speeds. However, the longer term
benefit expected was in training, staff development and internal communication. The Bottom Line: Dynamic testing and validation of
the design were essential to the success of the project. Investment requirements
were reduced in some areas, but additional needs were identified in other
system elements if the design was to meet performance objectives. The
models are now being used by Walkers for staff training, continuous improvement
and internal communication. CASE 4 - Ryder Logistics and Unilever Bestfoods The Challenge: As a provider of logistics services for Unilever in Brazil, Ryder Logistics sought ways to more closely integrate a warehouse with the production plant of its client. In doing so, Ryder also hoped to reduce its own costs in providing a complete transport and supply chain solution. Unilever Bestfoods was attempting to deal with larger volumes in receiving, storage and transport. As one of the world's largest third-party logistics suppliers, Ryder was responsible to receive and store finished products before expediting them on to customer distribution or receiving facilities. A key cost element was the operation of an external warehouse. By applying Activity Based Costing, Ryder hoped to better understand its cost structure and develop improved policies for storage, picking and shipment. An assessment of storage space assigned to specific product lines was expected to be an important element of this effort. Initial dimensioning of the relative spaces was performed using standard spreadsheet tools. When this dimension data was fed into a dynamic model, however, bottlenecks occurred in picking and the transfer of materials between locations. Additionally, several products were seen to require less space than expected. Alternative scenarios using different combinations and resource allocations led to a warehouse plan that was able to meet key cost and performance objectives. The Dynamisis partner was also able to help Ryder determine the number of additional docks that would be required to support the new plan. Managers from Unilever Bestfoods were also able to study the models and expressed confidence that Ryder's plans would meet expected future requirements. The Bottom Line: Ryder was able to reduce its own costs
and increase its responsiveness by using dynamic models to test various
customer volume and product mix scenarios. It was also able to increase
client confidence in its ability to keep pace with future increases in
demand. Capital Investment Justification - An SME Example CASE 5 - Burbidge & Son Ltd. The Challenge: Operational change is becoming a way of life for small- and medium-size enterprises that must continually strive to stay ahead of the competition. Trying new ideas out in the factory can take time, cause disruption, and be very costly, especially if they do not work first time. In a climate of tight financial pressures, few companies can afford new equipment investments that fail to deliver the anticipated benefits. The obvious solution is to experiment with alternative layouts and evaluate new equipment in a realistic model before making the changes in real life, but many small companies mistakenly assume that these approaches are only available to big business. An established manufacturer, Burbidge & Son supplies wooden kitchen unit doors and wood features to independent retailers who assemble these into complete 'top-of-the-market' kitchens. Employing120 people on two sites in Coventry, and with a turnover of about £12 million, Burbidge is typical of many small enterprises competing with foreign competitors in the UK market. As Graham Heaven, Burbidge's financial director notes, "We found ourselves in a shrinking market, due to the housing market downturn, and in some service aspects we had become uncompetitive in comparison with the importers. Realizing that we needed to significantly improve our ability to deliver complete orders and reduce delivery lead times, we started an investigation into our manufacturing and warehouse practices." In keeping pace with a market in which customers were demanding more product variety, Burbidge had seen its cost base rise and production times increase as its work shifted toward more small batch production runs. As it looked for solutions, the company recognized the need for detailed dynamic analysis to fully assess specific changes and justify the associated capital equipment investment. Based on prior success with the approach and desiring a methodology that its own staff could apply in the future, Burbidge contracted with the local Dynamisis partner to help with development of detailed models and staff training. An important consideration was that the partner would also be available for additional support and consulting services, if required in the future. "Although we have only a limited in-house IT resource," stated Heaven, "we felt that with the reduced cost of the hardware needed to run even advanced simulation software (a standard PC), and the far more user friendly nature of modern systems, bringing the technology in-house would be feasible and practical. This approach also meant that we would not be paying for a one-off project, and that we would be able to apply the technology to a range of business problems, some of which could not justify using the technology in their own right. We have found ProModel to be very intuitive to use, and this enabled our in-house staff to become proficient after the core training programme. It also means that it will be possible for users to quickly get back up to speed on it, even if there are long periods between projects." Initial application of the approach was to the company's paint and finishing line. A complex combination of staining, lacquering and drying required up to four passes through the line for each door. At batch sizes of 200, this is essentially an efficient continuous process, but with smaller batches of 50-100 the line is less than fully utilized and workers are often idle. The resulting increase in unit costs was substantial. The team used dynamic models to evaluate several options for splitting up the line to accommodate a wider range of batch sizes. Using actual production data, the models created a far better understanding of the existing process and highlighted some obvious unnecessary and wasteful activities. Simply splitting the line, which would require minimal capital investment, would increase output by 17% without increasing cost. However, by combining these changes with a major investment in a new lacquering pen, the analysis predicted that output could be increased by 33%. "The simulation project has provided exactly what we needed, clear and detailed answers about what proposed changes could achieve. We now have to make the final decision, incorporating other business factors, as to which way to proceed. But, either way, we can now put forward to the company board a firm proposal for major alterations to the paint line that we know will significantly increase our efficiency and reduce costs," states Heaven. He adds, "With these improvements potentially costing upwards of £500,000 to implement, we need to be certain that we make the right changes, the first time. This is what using simulation is helping us to achieve, at a cost that is just a small fraction of our proposed process investment. Furthermore, simulation has not only helped with assessing the options, the visual accuracy and animation of the model is a powerful communications tool that is proving extremely useful for explaining the proposed changes and getting commitment to them." The benefits to Burbidge of its decision to invest in dynamic modeling have been confirmed by another project which it was able to undertake on its own. A decision to replace door-edge profiling equipment with one of two different options also came up against batch size considerations, along with issues of cycling and set-up times. By undertaking the model development and then the analysis, the company achieved a far greater understanding of the overall process. While initial findings suggested that the twin cutter machine was far more efficient with existing production demands, Burbidge also found that variations in batch size had a marked effect on performance, with a single cutter machine being the more efficient when the batch sizes are below 100. Using this detailed data, a justifiable decision was made to actually two machines, one of each type. Again, model data proved crucial in helping management to justify a better decision, no small issue for capital project in excess of £350,000. The Bottom Line: The key benefit for Burbidge was the
ability to test a variety of capital equipment upgrade proposals and justify
expenditure decisions with certainty that the outlays would result in
the output increases or cost reductions expected. Heaven sums it up well:
"Too often, companies make process change or investment judgments
based on gut feel, or extremely simplified and inaccurate assessments,
and then wonder why these changes fail to meet expectations. Yet, as we
have found, the tools for enabling important operational decisions to
be based on realistic data are now readily available, easy-to-use, and
require only a relatively small investment - especially compared to the
cost of getting it wrong." Knowledge Transfer in Health Care CASE 6 - New Patient Care Processes in China The Challenge: Experts working to support development in emerging economies are often faced with the need to demonstrate new processes, introduce new technologies or teach new management concepts to individuals who do not share a common basis for understanding. Issues of language, culture and local experience complicate this transfer of knowledge. Effective instruction requires techniques that provide a common reference against which both sides can explain their ideas, patterns and traditions. A well-respected group of U.S. health care consultants was asked to develop the design for a new private hospital in one of China's largest cities. Recognizing the need for architectural form to follow function and understanding that a private facility would need to provide higher levels of service than state-run hospitals, the consulting team considered how to convey new approaches to patient care processes in a way that would overcome the expected barriers to communication. A project leader suggested the use of dynamic models that could visually represent new processes and concepts. Three key elements of the new facility were identified for substantial process changes compared to traditional practice in public hospitals. In day clinics, patients often complained of extremely long waiting times and short exams with little explanation. Patients perceived high barriers to access and had little privacy. The consulting team quickly recognized that better use of exam rooms and offloading of some physician activities to an enlarged and better-trained nursing staff could free up time to provide a more complete and patient-sensitive diagnosis. An initial model followed a single patient through the proposed new process, showing each interaction with the medical staff. Nurses, who had been silent during most of the initial discussions, became quite engaged as they pointed out where the proposed process differed from traditional patterns. The consulting team was able to draw out information about the reasons behind these practices, allowing the experts to fine tune the new process to meet local sensitivities. A second model compared the new approach with established patterns, demonstrating for hospital managers that expected patient volumes could be maintained-even while reducing waiting times and providing more quality time with physicians. Also highlighted was the potential benefit of scheduling patients compared to taking them on a walk-in basis. A radiology and imaging center with up-to-date equipment was also considered an essential part of the new facility. Because the cost of these devices was as high in China as in developed nations, efficient use of the equipment to handle as many patients as possible was seen as a key factor in justifying the required investment. Here again, an initial model was used to show the optimal process for each major category of imaging study. A "typical day" was then simulated to demonstrate patient throughput levels and estimate the revenue expected. Finally, the consulting team presented the proposed design for a new surgical center, where effective use of limited space and careful attention to infection control were considered key objectives. Dynamic models demonstrated the importance of moving invasive cardiology, endoscopies and minor procedures into dedicated rooms to free up operating theatres. The experts also presented a novel approach in which the same spaces could be used for pre-operative preparation of patients and post-op care. Finally, they used the models to explain a case cart system that would reduce damage and eliminate the need for separate corridors dedicated to sterile and contaminated surgical instruments. The medical staff was clearly able to understand the new processes and the concepts proposed, but the Dynamisis approach was also able to stimulate discussions among doctors, nurses and administrators about their concerns, needs and priorities. In some cases, differing perspectives were balanced against each other in ways that facilitated group commitment to a unified approach. Sensitive use of the models to draw out information about local practice served to enhance the credibility of the foreign advisor team and allowed them to adapt their recommendations to the values of the client and future patients. The Bottom Line: Although the Dynamisis methodology often uses very detailed studies to help clients reduce patient wait times or improve facility utilization, dynamic models also provide a visual reference for individuals from very different perspectives to reconcile their viewpoints. Hospital administrators, physicians and nursing staff are able to use animated models and on-screen performance indicators to convey their concerns, overcome sub-optimization in one area at the expense of others, and work together with an agreed strategy toward better patient care. |
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