PACKING LINE SAVINGS IN THE FOOD AND DRINK INDUSTRY

Transcription

1 GG243 GUIDE ENVIRONMENTAL TECHNOLOGY BEST PRACTICE PROGRAMME PACKING LINE SAVINGS IN THE FOOD AND DRINK INDUSTRY GOOD PRACTICE: Proven technology and techniques for profitable environmental improvement

2 PACKING LINE SAVINGS IN THE FOOD AND DRINK INDUSTRY This Good Practice Guide was produced by the Environmental Technology Best Practice Programme Prepared with assistance from: Enviros March Crown copyright. First printed September This material may be freely reproduced in its original form except for sale or advertising purposes. Printed on paper containing a minimum of 75% post-consumer waste.

3 SUMMARY Poor design and operation of packing lines lead to waste product, waste packaging, excessive reworking and increased labour costs. All of these cost money and reduce profits. Many companies lose as much as 4% of their product and packaging through inefficient packing lines - losses that can be worth thousands of pounds a year. To meet increased demand, some companies invest in new equipment even when existing equipment could have done the job if its efficiency had been improved. This Good Practice Guide is intended to help companies reduce their operating costs or even avoid or delay the need to invest in new equipment. Taking action to improve packing line efficiency will save money by: reducing product and packaging waste; improving productivity; increasing production capacity. The Guide describes a step-by-step approach to improving packing line efficiency. It explains how to: measure packing line performance; understand the symptoms of poor packing line performance; locate problems with individual machines; focus efforts to improve efficiency in the right areas; reduce product and packaging wastes. A worked example based on a hypothetical, seven-stage jam packing line is used to illustrate the approach. Industry Examples throughout the Guide demonstrate the significant benefits of taking action to improve packing line efficiency.

4 CONTENTS Section Page 1 Introduction The aim of this Guide 1 2 Step 1 - Map the process Principles of packing line design Putting the principles into practice by mapping the process flow Interpreting the design values curve on the v-graph 7 3 Step 2 - Calculate performance indicators Causes of reduced packing line performance Measuring key performance indicators 11 4 Step 3 - Investigate individual machine speed Best observed speed Interpreting the observed values curve on the v-graph 19 5 Step 4 - Investigate individual machine availability What is meant by availability Types of below capacity running Carrying out an event study Calculating availability from an event study Checking the validity of the event study Completing the v-graph by plotting effective values Interpreting the completed v-graph 26 6 Step 5 - Identify key problem areas Analysing the v-graph 30 7 Step 6 - Identify root causes of problems Root cause analysis 32 8 Step 7 - Take corrective action Identify a solution Develop an Action Plan Implement corrective actions Continue to improve 36 9 Action Plan 38 Appendices Appendix 1 Glossary 39 Appendix 2 Blank templates 41

5 1 INTRODUCTION Packing line efficiency is an important part of cost control in the food and drink industry. Inefficient packing lines lose many companies as much as 4% of their product and packaging - a loss worth tens or hundreds of thousands of pounds a year depending on the product. In some cases, companies even invest in new equipment to meet product demand when their existing equipment could have done the job if its efficiency had been improved. 1 Poor design and operation of packing lines result in: waste of product and packing materials; lines operating below capacity; excessive reworking of off-specification product; reduced production efficiency. This waste of effort and materials costs money and reduces profits. This Good Practice Guide aims to help all sizes of company in the food and drink industry save money by improving their packing line efficiency. Because the consequences are obvious and immediate, companies tend to take action only when a packing line stops completely for several minutes. Shorter stoppages and slow running are frequently ignored, even though they typically make up over half the downtime. Long stoppages are often caused by random events, eg a chain snapping or a motor failing. Short stoppages are generally more predictable and, therefore, more controllable. Gaining a better understanding of packing line performance will help companies to increase their profits by: reducing the waste of product and packaging on packing lines; improving the productivity of equipment; increasing production capacity to avoid, or at least delay, the need to invest in new packing line equipment. How well are your packing lines performing? 1.1 THE AIM OF THIS GUIDE Industrial packing lines are not always designed in line with the basic principles of good operation. Companies often make do with old equipment, use second-hand plant and mix and match equipment to create new capacity or save money. Even lines that were initially well designed may shift with time away from good design and operation, eg fail to keep pace with changes in products or production patterns. This Guide explains how to identify the root causes of packing line problems and then how to eliminate them. It describes a step-by-step approach to help companies: measure the performance of their packing lines; recognise the symptoms of poor packing line performance; identify where problems occur on their packing lines; 1

6 focus their efforts to improve efficiency in the right areas; reduce product and packaging waste. This step-by-step approach (see Fig 1) has two distinct themes: 1 Regular measurements of the performance of the line as a whole. The key performance indicators described in Section 3.2 show when the line is not performing well and highlight the need to take a detailed look at individual machines. Specific investigation of the performance of individual machines. The steps described in Sections 4-8 will help companies to identify the real causes of poor line performance and to investigate appropriate solutions. The core of this investigation is the v-graph (see Section 2.1). This includes three elements which indicate problems in specific areas of the packing line, ie: - the design values curve shows whether individual machines have been specified correctly; - the observed values curve shows whether individual machines are operating at specification; - the effective values curve shows whether individual machines are operating reliably, and how this affects overall line performance. STEP 1 Map the process How well is your packing line designed? Plot DESIGN values on the v-graph. Monitor performance indicators regularly and continue to improve. STEP 2 Calculate performance indicators Do you have a problem with your packing line? Identify factors affecting performance. Compare performance indicators with historical and best practice records and decide if further investigation is needed. STEP 7 Take corrective action STEP 3 Investigate individual machine speed Are plant items performing to design? Plot OBSERVED values on the v-graph. STEP 6 Identify root causes of problems STEP 4 Investigate individual machine availability How reliable are plant items? Plot EFFECTIVE values on the v-graph. STEP 5 Identify key problem areas Analyse the v-graph. Fig 1 Step-by-step approach to improving packing line efficiency Advice on other packaging issues is given in: Good Practice Guide (GG140) Cutting Costs and Waste by Reducing Packaging Use Good Practice Guide (GG141) Choosing and Managing Re-usable Transit Packaging Good Practice Guide (GG157) Reducing the Cost of Packaging in the Food and Drink Industry A summary of this Guide, How to Improve Packing Line Efficiency in the Food and Drink Industry (ET243), is also available. All these and other publications from the Environmental Technology Best Practice Programme are available free of charge through the Environment and Energy Helpline on freephone

7 2 STEP 1 - MAP THE PROCESS STEP 1 Map the process How well is your packing line designed? Monitor regularly and continue to improve. STEP 2 Calculate performance indicators Do you have a problem with your packing line? 2 STEP 7 Take corrective action STEP 3 Investigate individual machine speed Are plant items performing to design? STEP 6 Identify root causes of problems STEP 4 Investigate individual machine availability How reliable are plant items? STEP 5 Identify key problem areas This Section outlines the principles of good packing line design. It describes how to map the process and plot the design values on a v-graph. This v-graph (see Section 2.1.2) is a simple but powerful diagnostic tool which shows whether individual machines in the packing line have the correct capacities or design speeds for good line operation. Sections 4-6 explain how to analyse the performance of individual machines by plotting additional curves on the v-graph. 2.1 PRINCIPLES OF PACKING LINE DESIGN A packing line is made up of different pieces of equipment (eg jar sorters and washers, filling heads, cappers, labellers and packers) performing specific operations to deliver the final packed product. They are linked together by conveyor lines and/or manual handling processes, and are usually controlled by sensors and control equipment. A packing line needs to be considered as more than just the sum of its parts. Individual machines need to be specified correctly so that each machine works with all the others as part of an efficient overall design. This Guide is not intended to be a definitive design manual for packing lines, but to point to key considerations, ie: the bottleneck machine; the shape of the v-graph; the buffer capacity provided by accumulators and conveyors The bottleneck machine Over extended periods, the speed of the line as a whole cannot exceed the speed of the slowest machine. For obvious reasons, this is called the bottleneck machine. Each machine on a packing line is designed to run at a particular production rate or capacity. The design speed is often quoted 3

8 in items, eg jars/minute, or sometimes as a speed, eg metres/minute. Although common sense might suggest that all machines should have the same design speed, this is not good design. The first stage in good packing line design is to decide which machine should be the bottleneck. For example, a filling machine connected to a manufacturing operation may have a limit on how fast it can be run which is independent of the operation of the packing line. Alternatively, it may be important to maximise return on capital for the most expensive machine. The bottleneck machine should be the one considered, for reasons of production, quality, cost, etc, to be the most important to keep running as close to its maximum capacity as possible. 2 To ensure the desired machine is the bottleneck, all other machines must have a higher design speed. The rest of the line should be designed to service the bottleneck machine and to keep it running as constantly as possible. This means the bottleneck machine should ideally: never be starved of feedstock, ie there should always be raw materials waiting to be processed at the input to the bottleneck machine; never be stopped due to build-back, ie the processed product from the bottleneck machine should be taken away fast enough to avoid product building up and blocking the output from the bottleneck machine. This means specifying the design speeds of each machine in the packing line so as to form a v-shape (see Fig 2), and building in appropriate buffer capacity (see Section 2.1.3). The design speed of the bottleneck machine determines the overall speed of the packing line and is thus the line design speed The v-graph shape In this Guide, the machines before the bottleneck machine are described as upstream and those after the bottleneck machine as downstream. To give the desired v-shape, both upstream 1 (the machine feeding materials to the bottleneck machine) and downstream 1 (the machine taking away product from the bottleneck machine) should have higher design speeds than the bottleneck machine. Upstream 2 (the machine feeding materials to upstream 1) should have a higher design speed than upstream 1, and downstream 2 (the machine taking away product from downstream 1) should have a higher design speed than downstream 1. Continuing to apply this principle will build up a v-shape. The v-shape ensures that: Each upstream machine is capable of feeding materials to the next machine faster than it can cope with. It should, therefore, never be starved. Each downstream machine is capable of taking away product from the previous machine faster than it can produce it. It should, therefore, never suffer from build-back. Fig 2 shows the v-graph of design speeds for a hypothetical packing line in a jam-making factory. This seven-step, dedicated packing line, capable of filling 250 g or 1 kg jars, is used throughout the Guide to illustrate the step-by-step approach. In practice, speed differences between machines are limited by economics - with a machine typically rated 5-15% faster than its neighbour. Line control with a v-shape A control system is essential with the v-shape. If each upstream machine was allowed to run at its design speed all the time, then the input to the following machine would be overloaded - causing blockages or overflows and spillages/breakages. The inputs of all machines should be fitted with sensors set up to switch off the machine immediately upstream when the feed level gets too high. 4

9 300 Machine speed (units/minute) (jars/minute) Design speed Upstream 3 Upstream 2 Upstream 1 Bottleneck machine Downstream 1 Downstream Downstream 2 3 Depalletiser Jar sorter Jar washer Filler head Capper Labeller Packer Fig 2 V-graph for an example seven-step packing line It takes time for items to move from one machine to the next along a conveyor, causing an inherent lag or delay between the sensor signal at the input to a machine and the results of the control action at the previous machine. To ensure the sensors are positioned correctly and that the control logic is appropriate, it is necessary to understand how the control system works and the implications for the conveyor system linking each machine. In the Industry Example in Section 5.7, a badly positioned sensor reduced line efficiency by 10%. If all machines are running smoothly, then the average throughput of each machine will match the throughput of the bottleneck machine. With a v-shape, this means that the downstream and upstream machines are sometimes idle. The control system will cause upstream machines to idle (or be switched off) while waiting for the machine immediately downstream to clear the conveyor between them. Because they have a higher design speed than the preceding machine, downstream machines will sometimes have no materials to process and will have to idle, waiting for machines immediately upstream to produce materials to process. The v-shape thus means that upstream machines have build-back time designed in and that downstream machines have starvation time built in Buffer capacity: accumulators and conveyors The v-shape also means that conveyors between upstream machines tend to fill up with items and those between downstream machines tend to be relatively empty. Conveyors thus provide a limited amount of buffer capacity to help keep the bottleneck machine running if a machine breaks down or stops. When an upstream machine stops, the items on the conveyor will keep the following machine running for a finite time. When a downstream machine stops, the preceding machine will keep running until it has filled up the conveyor. It is important to consider what will happen if the packing line breaks down or stops due to mechanical problems or materials/packaging running out and to decide whether the conveyor has sufficient buffer capacity, or whether you should design in additional buffer capacity. Some packing lines are designed with additional buffer capacity in the form of storage areas for materials - known as accumulators - between machines. Cost generally limits the number of accumulators to two (one upstream and one downstream). Fig 3 shows a typical arrangement of accumulators on a packing line, ie immediately before and after the bottleneck machine. 5

10 Upstream machine Normal operation Machine failures Upstream machine Accumulator Accumulator 2 Bottleneck machine Accumulator Bottleneck machine Accumulator Downstream machine Downstream machine Key: Full Empty Fig 3 Arrangement of accumulators on a packing line Under normal operating conditions, the upstream accumulator in Fig 3 is kept full and the downstream accumulator is kept empty. If the upstream machine fails, the bottleneck machine can draw on feedstock from the upstream accumulator and thus keep running while the problem with the upstream machine is resolved. When the upstream machine comes on line again, it takes over feeding the bottleneck machine and the accumulator gradually refills. However, this scenario is only possible for a packing line with the correct v-shape, ie the upstream machine can run faster than the bottleneck machine. Similarly, if the downstream machine fails, the output from the bottleneck machine is diverted to the downstream accumulator. When the downstream machine comes on line again, the downstream machine takes over the output from the bottleneck machine and empties the accumulator. 2.2 PUTTING THE PRINCIPLES INTO PRACTICE BY MAPPING THE PROCESS FLOW Why map the process flow? A clear understanding of how the packing line operates can be achieved by drawing a simple process flow diagram. This diagram will also provide a framework for showing how each part of a process affects the other parts. It should show what each machine does and where it fits into the packing line. If subsequent analysis reveals that poor efficiency is related to the packing of a particular brand/size/format of product, then all future work should concentrate on that brand/size/format How to map the process flow Fig 4 shows the process map for the hypothetical packing line in a jam-making factory. Optional equipment is used to pack the two jar sizes. A simple process flow diagram such as the one shown in Fig 4 can be sketched out in five minutes by someone who knows the line. However, with complex multi-product lines it can be helpful to 6

11 1 kg filler head Large capper Case packer Depalletiser (jars) Jar sorter Jar washer 250 g Filler head Small capper Labeller Tray packer Fig 4 Process map of the example jam packing line carry out more thorough mapping first and then use this to produce a simplified diagram. A more detailed map also provides information that can be useful for future troubleshooting. Start by understanding the current layout of the packing line. Walk through the packing line area and sketch the physical arrangement of the equipment on a rough map. Also estimate key distances and operating parameters. This information will provide a basis for recording all operations associated with the packing line. For example, conveyor line lengths and speeds are useful when determining the line s buffer capacity. Note any points on the line where it branches between different options or there are changes in direction of flow. These are often problem areas. Add more detail to the map using the information available in line plans, layout diagrams, wiring diagrams and Hazard Analysis Critical Controls Point (HACCP) studies. 2 The process map should: Show normal operation, ie what the packing line normally packs and how it is arranged to do that. For example, a wrapping machine may only be used in conjunction with another machine or for a particular product. Reflect the different routes used for different products (eg using different colour lines/text). In practice, a line may be used to pack different sizes of product, different types of product and/or different brands. Each variation may have an impact on the packing line. For example, the line speed may be varied for different product sizes. Identify points where product and/or packaging are rejected (for whatever reason) by talking to the operators. Rejects are symptoms of packing line efficiency problems and are sources of waste. These points may include: - built-in quality checkpoints; - other points where regular packaging problems occur (where these are known). Individual process flow diagrams dedicated to a particular variation of brand/size/format may be helpful for complex operations. 2.3 INTERPRETING THE DESIGN VALUES CURVE ON THE V-GRAPH Each of the main processes identified on the process map should be a point on the x-axis of the v-graph. The design curve of the v-graph is produced by plotting the design speed given in the manufacturer s specification for each machine (see Fig 2). A template for plotting v-graphs is given in Appendix 2. A v-graph should be plotted for each line configuration. For example, the v-graph shown in Fig 2 shows only the main branch for the example jam packing line shown in Fig 4 (ie the 250 g jars). A separate v-graph would be needed for the line packing 1 kg jars. 7

12 Should the design values curve turn out not to be v-shaped around the bottleneck machine, do not take immediate corrective action until operational factors have been taken into account. Replacing or upgrading machinery to produce a satisfactory v-shape can be expensive. Operational factors are sometimes a more significant cause of poor packing line performance, and may be much more costeffective to address. Not taking action until all the steps in Fig 1 have been completed will ensure the most cost-effective improvements are implemented. 2 8

13 3 STEP 2 - CALCULATE PERFORMANCE INDICATORS STEP 1 Map the process How well is your packing line designed? Monitor regularly and continue to improve. STEP 2 Calculate performance indicators Do you have a problem with your packing line? STEP 7 Take corrective action STEP 3 Investigate individual machine speed Are plant items performing to design? 3 STEP 6 Identify root causes of problems STEP 4 Investigate individual machine availability How reliable are plant items? STEP 5 Identify key problem areas In practice, there are good reasons why even a well-designed packing line with design speeds forming a v-shape around the bottleneck machine will not operate at full capacity. This Section discusses the factors that reduce packing line efficiency and explains how to make some simple performance measurements. These measurements will help to highlight problems and allow companies to identify opportunities for improvement. This Section of the Guide: Describes how overall packing line performance deteriorates due to: - lost time; - reduced speed; - poor quality. Explains how to quantify these effects by calculating key performance indicators. These indicators can be used to build up a historical record for use when monitoring changes as part of a continuous improvement process. 3.1 CAUSES OF REDUCED PACKING LINE PERFORMANCE In theory, a packing line designed with a perfect v-shape should run at the design speed of the bottleneck machine. For example, the bottleneck machine in the example jam packing line shown in Fig 4 (see Section 2.2.2) has a design speed of 200 jars/minute. The hypothetical factory operates from 9 am to 5 pm and nominally has an 8-hour working day. Its theoretical maximum production rate is, therefore, 200 jars x 8 hours x 60 minutes = jars/day. Real packing lines seldom get close to this theoretical maximum performance. Fig 5 shows how lost time, reduced speed and poor quality reduce the quantity of saleable product produced (ie net production rate) of the example jam packing line to only jars/day, ie only around 56% of the theoretical maximum. Each of the causes of reduced packing line performance shown in Fig 5 can be quantified as a key performance indicator (see Section 3.2). 9

14 External lost time Downtime The whole line stops running for 1.25 hours because of outside factors, eg lunch breaks, meetings, lack of supply (due to late delivery or manufacturing problems) and major line stoppages (due to poor batches of material or manufacturing quality problems). 3 Reduced speed The whole line stops running or produces unsaleable product for 1.5 hours due to factors within the line, eg machine breakdowns, blockages from poor handling of packaging or materials, and set-up time between runs. The average rate at which product comes off the line during normal running (ie excluding downtime) is only 175 jars/minute. This is caused by short stoppages on individual machines creating starvation or build-back at the bottleneck machine or at the end of the line. Poor quality During normal running, 3% of product (1 525 jars/day) is rejected at the end of the line or at key quality measurement points. NB To avoid double counting, this figure does not include rejects during periods when the whole line is down. Fig 5 Causes of reduced performance by the example jam packing line When trying to optimise packing line performance, it is important to understand and take account of the causes of poor performance. If the main reduction is due to external lost time, then attention should be given to factors outside the packing line. Similarly, it is unlikely to be costeffective to try to increase the line s average rate by buying faster equipment or investigating short Adjusting machine speed produces savings of over /year Weekly monitoring of key performance indicators at a UK sweet manufacturer revealed a large variation in the efficiency of a packing line used to bag the sweets. When the performance of the packing line was analysed, the company discovered the machine speed was at fault. This caused inaccurate weighing of product and failure of heat-sealing equipment, leading to partially filled bags of perfectly good product being rejected. A study found that the annual reject rate was over 11 million bags of sweets. Adjusting the machine speed solved the problems of inaccurate weights and poorly sealed bags. The benefits of this simple change include: reduced reject rates worth over /year in saved product, packaging and waste disposal costs; around 500 tonnes/year less waste sent to landfill; avoided rework costs (including labour, utility use and material consumption) worth /year; increased production output and capacity. Solving the packing line problem saved over /year - for just the negligible cost of the time taken to investigate and adjust the speed of the machine. 10

15 stoppages when the main reason for poor line performance is, in fact, downtime due to frequent breakdowns. It may be more appropriate to improve maintenance or to replace those parts of the line that are fast but break down frequently (providing the v-shape is maintained). Similarly, it may actually be better to reduce the line speed if this improves quality and reduces the reject rate. 3.2 MEASURING KEY PERFORMANCE INDICATORS Five key performance indicators can be used to identify poor packing line performance. These indicators and other key parameters are defined in the Glossary in Appendix 1. To measure key performance indicators, observe and record instances of poor overall running of the packing line. Measurements of key performance indicators should be performed routinely, eg weekly. Choose an extended period such as a shift or an entire working day that coincides with the collection of data for other routine measurements such as net production (see Section 3.2.4). The main measurements need just a stopwatch and a clipboard. Note how long the line stops (or produces 100% scrap product) and the causes. 3 Recorded reasons for poor performance may have to be altered after further investigations. For example, a stoppage recorded initially as downtime because the filler head stopped the whole line running may turn out to be due to a problem with the manufacturing process (eg the jam was outof-specification and too thick for the filler head to process). In this case, the cause of the stoppage may be changed to external lost time. Similarly, the reduced speed of the line as a whole may be due to the jars taking longer to fill because the jam was slightly too thick but not thick enough to cause a stoppage. Again, this is not the fault of the packing line equipment. Indicators should be defined and measured to match requirements. They are not rigorous scientific parameters, merely tools to identify causes and solutions. The example calculations shown below for the five key performance indicators are based on the hypothetical seven-step jam packing line featured earlier in the Guide Key performance indicator: external lost time This indicator shows the impact on the packing line of external factors such as meetings, lunch breaks and supply failures from outside the packing line due to manufacturing problems. Accounting for lost time caused by factors outside the packing line ensures that other performance indicators give a true picture of how the packing line itself is performing. The external lost time indicator shows the proportion of the working day (ie the hours the site is open) that the packing line could have run after subtracting external lost time. External lost time indicator = Working day External lost time = Potential run time Working day Working day Example calculation The working day was from 9 am to 5 pm, ie 8 hours. This included a 1-hour lunch break and 15 minutes when the supply of jars ran out and more had to be fetched from the warehouse. Using this information in the equation gives: External lost time indicator = 8 hours (1 hour + 15 minutes) = 6.75 hours = hours 8 hours 11

16 This calculation shows that the packing line was available for 84% of the day and unavailable for 16% of the day owing to external factors. The potential run time, ie the time the packing line could have run after subtraction of external lost time, is 6.75 hours Key performance indicator: downtime This indicator shows the impact on the packing line of stoppages within the packing line such as breakdowns, blockages, product run-outs and product changeovers. These internal stoppages are termed downtime. Downtime also includes periods when 100% of the production is scrap owing to packing line problems. 3 The downtime indicator shows how long the packing line actually runs (ie after subtracting downtime) as a proportion of the potential run time. The indicator provides useful pointers to reliability problems within the packing line. These may be the result of maintenance requirements, out-of-specification material or packaging, or less than optimum changeover and set-up procedures. Such problems may show up as equipment breakdowns, material blockages and excessive time for set-up and product changeovers. Downtime indicator = Potential run time Downtime = Run time Potential run time Potential run time Use a stopwatch to time the duration of incidents that qualify as downtime and note likely causes. Example calculation As well as the external lost time, there was a stoppage of 30 minutes to fix a breakage on the capper, three 10-minute stoppages because of an upside-down jar, two 10-minute stoppages due to a motor trip on a conveyor, and one 10-minute stoppage because of a cap wedged in a feeder. The total downtime is 1.5 hours and, as calculated earlier, the potential run time is 6.75 hours. Using this information in the equation gives: Downtime indicator = 6.75 hours ( minutes) = 5.25 hours = hours 6.75 hours This calculation shows that the line ran for 78% of the time it could have done without any stoppages within the packing line. Downtime is, therefore, 22%. The actual run time, ie the time the packing line actually ran after subtracting external lost time and downtime, is 5.25 hours. A downtime of 22% may be acceptable if there are several changeovers between types of jam or several set-ups because of different sizes of jar. In this case, measurements were taken during a shift when only one product and one size of jar were being processed. The value of the indicator, therefore, suggests poor reliability. The causes of the stoppages could point to old and worn machinery or possibly out-of-specification materials, eg caps too large. The Industry Example opposite describes a more complex situation where measuring the downtime indicator led a company to modify its changeover and set-up procedures. 12

17 Baby food manufacturer reduces downtime A baby food company in the North West introduced a new packing line for a range of cereal products. Measurements and investigation of downtime showed that the company was suffering significant performance losses as a result of non-optimal procedures during the 500 product changeovers per year. All the tasks necessary during product changeover were listed and analysed. The production team was then observed performing these duties. The key to a new method of working was to identify which tasks could be performed concurrently during product changeovers. To achieve improvements in efficiency, tasks that did not overlap were assigned to different members of the production team. Task cards were prepared that listed each person s duties during the changeover period, together with a reminder to help other people when their jobs were complete. The new working method reduced the time spent on product changeover significantly. Average downtime for a product changeover has fallen from typically 2 hours to less than 20 minutes, thus reducing downtime by up to 10%. This has allowed the company to achieve the extra production capacity needed to meet product demand merely for the cost of some operator and management time Key performance indicator: reduced speed This indicator shows the impact on the packing line of periods when the line is working at reduced speed. It shows the average recorded line speed during the run time as a proportion of the line design speed. The run time is the part of the measuring period when the line runs normally, ie excluding periods of external lost time or downtime. The reduced speed indicator provides useful pointers to a number of problems and their possible solutions. A low value could mean that equipment is running slowly due to: mechanical reasons, eg a worn-out bearing or a burnt-out motor winding; material reasons, eg the consistency of the product being packed or the thickness of the packaging material; control reasons, eg the control system is introducing delays over and above the designed build-back and starvation time. Reduced speed indicator = Average line speed Line design speed = (Quantity produced Run time) Line design speed = Quantity produced Line design speed x Run time Since run time excludes external lost time and downtime: Run time (as a proportion = Working day External lost time Downtime of working day) Working day 13

18 Example calculation Total net production during one day was recorded as jars. In addition, rejects were produced, giving a total of jars produced. There were no downtime rejects. The line design speed is 200 jars/minute. As calculated earlier, the run time is 5.25 hours. Using this information in the equation gives: Reduced speed indicator = Quantity produced Line design speed x Run time = ( ) jars/day 200 jars/minute x 5.25 hours/day = jars/day (200 x 60) jars/hour x 5.25 hours/day 3 = jars/day jars/day = 0.88 This calculation shows that the packing line is running at only 88% of its design speed. Plotting the v-graph (see Section 2.1.2) will help to identify which machine is causing the reduced line speed. Then investigate whether the cause is mechanical, whether it is related to the packing material or product, or whether it is a control fault Key performance indicator: quality This indicator shows the proportion of units coming off the end of the packing line during the run time that are within specification and thus saleable, ie the proportion that is net production. A low value points to poor equipment operation, eg plant not meeting specification due to wear and tear, or incorrect running speed. It can also highlight material problems such as slightly out-of-round (oval-shaped) caps that sometimes do not seal properly. Most companies measure net production directly through an on-line counter or infer it from warehouse records. Measuring net production normally only involves either checking the running totals on counters at the start and the end of the measuring period, or selecting a measuring period that coincides with standard packing line data points (usually the start and end of shifts). Many companies also measure total units rejected (to give total gross production), directly from counters on the line. Alternatively, the quantity of product going to rework or disposal can be estimated or the number of units rejected during a representative period recorded manually on a tally sheet. Quality indicator = Net production Net production + Rejects where rejects are the number of units rejected for quality reasons during run time, ie excluding unsaleable units produced during downtime. 14

19 Example calculation Total net production during one day is jars and rejects are produced. There are no downtime rejects. Using the information from above in the equation gives: Quality indicator = jars/day ( ) jars/day = jars/day jars/day = This calculation shows that 97.2% of saleable product is produced during actual run time (ie excluding external lost time and downtime). This means that 2.8% of output is rejected during run time - a value that indicates that action to improve product quality and reduce rejects is worthwhile (see Section 7) Key performance indicator: effectiveness This indicator shows how well the packing line is running overall compared to how well it should run in a perfect world. It gives a single value that summarises the actual overall performance of the line once the effect of external influences (ie external lost time) has been removed. The effectiveness indicator shows the actual saleable production (ie net production) as a proportion of the potential production, ie the total number of units the line could produce if it operated with no downtime, no loss of speed and no quality rejects for all of its potential run time. 3 Effectiveness indicator = Net production Potential production (over potential run time) This is the same as saying: Effectiveness indicator = Downtime indicator x Reduced speed indicator x Quality indicator If there are no downtime, no speed losses and no quality rejects, the three respective indicators will have a value of 1. This would give an effectiveness indicator of 1, indicating that the line is 100% effective. Example calculation Earlier calculations produced values of 0.78 for the downtime indicator, 0.88 for the reduced speed indicator and for the quality indicator. Using these values in the equation gives: Effectiveness indicator = 0.78 x 0.88 x = 0.67 This calculation shows that the packing line was 67% effective overall on the day the measurements were made. It is up to the company concerned to decide whether this is satisfactory. Deciding acceptable performance The definition of good overall effectiveness depends on a company s circumstances. A packing line that packs one format of one size of one brand might be expected to achieve a high overall line effectiveness - possibly 80% or more. A packing line with numerous brand/size/format changeovers each day will have a much lower overall line effectiveness - possibly as low as 45%. 15

20 Other factors that affect the overall line effectiveness include: - the age of the equipment; - the complexity of the packing line; - the degree of difficulty associated with the product being packed. As a rule of thumb, companies that have done nothing recently to improve their packing line performance should be able to improve their overall line effectiveness by 10% by following the approach described in this Guide. 3 16

21 4 STEP 3 - INVESTIGATE INDIVIDUAL MACHINE SPEED STEP 1 Map the process How well is your packing line designed? Monitor regularly and continue to improve. STEP 2 Calculate performance indicators Do you have a problem with your packing line? STEP 7 Take corrective action STEP 3 Investigate individual machine speed Are plant items performing to design? STEP 6 Identify root causes of problems STEP 4 Investigate individual machine availability How reliable are plant items? STEP 5 Identify key problem areas 4 The key performance indicators show how well the line is performing overall and thus whether there is a problem. The next step is to investigate which plant items are responsible for the line s poor overall performance and the possible causes. Investigating individual machines will also help companies that have not previously looked at the performance of their packing line to obtain a base-line. Causes of poor overall performance can be investigated by measuring two parameters for each individual machine and plotting two further curves on the v-graph. Best observed speed is a measure of the production rate of an individual machine at full operation. It indicates whether the machine is performing to specification. This Section explains how to measure the best observed speed and how to interpret observed values on the v-graph. Mean effective rate is a measure of machine availability. It is the proportion of time the machine runs at capacity, ie at its best observed speed. It indicates how reliably the machine is performing. The measurement and interpretation of mean effective rate are discussed in Section BEST OBSERVED SPEED This is the production rate of the machine when it is running as fast as it can, ie: there is no downtime; the machine is not running slow due to poor supply (starvation) or product not being taken away (build-back); there are no problems with mechanical components or materials. Measurements need to be made at a time when the machine is running under these conditions. In normal operation, the v-shape for good packing line design means that all machines except the bottleneck are idling for significant periods (upstream machines will experience build-back and downstream machines, starvation). On typical packing lines, individual machines tend to operate in 17

22 spurts (processing several items at full speed) and then stopping for an extended period rather than stopping for a short time after every item. Measurements, therefore, need to be made during the full speed spurt. If necessary, a spurt can be induced by deliberately loading or clearing conveyors. Accuracy is essential when measuring observed values: Measure the time taken for all the stages in a sequence, including pallet loading and manual operations (where applicable). The process may be partly manual and partly automated - in such cases it is important to measure the time taken to perform the whole procedure and not just the machine speed. When timing a set sequence of events, count 0 is when the measurement starts and count 1 is when the same point in the sequence is reached again (see Fig 6). Measuring the best observed speed of the filler head on the example packing line The following method was used to measure the best observed speed of the filler head (the bottleneck machine) in the example jam packing line. 4 Decide how many revolutions it is necessary to time to obtain an accurate measurement. Mark the filler head to enable revolutions to be counted. Ensure that, during the measurement period, the machine will be fed with material and product removed. Time the filler operation (see Fig 6). Find out how many jars were filled during each revolution. Number of revolutions counted = 10 revolutions Total time between stopwatch start and stop = 92 seconds Number of jars filled/revolution = 30 jars Number of jars filled during the measurement period = 300 jars Best observed speed = 300 jars/second 92 = 196 jars/minute Filler head Revolution: Start stopwatch Stop stopwatch Fig 6 Timing the filler head to determine its best observed speed 18

23 4.2 INTERPRETING THE OBSERVED VALUES CURVE ON THE V-GRAPH Fig 7 shows the v-graph for the example jam packing line with the design and best observed speeds plotted. When running at their best performance, most of the individual machines are close to their design values - apart from the capper (the downstream 1 machine). In fact, the actual speed of the capper is less than the filler. This measurement, therefore, suggests that the capper is the limiting process or bottleneck. However, measurement of best observed speed does not give the whole picture. When the effect of downtime is taken into account, the main problem may turn out to lie with a different machine (as shown in Section 5.7). 300 Machine speed (units/minute) (jars/minute) Design speed Best observed speed Upstream 3 Upstream 2 Upstream 1 Bottleneck machine Downstream 1 Downstream Downstream 2 3 Depalletiser Jar sorter Jar washer Filler head Capper Labeller Packer Fig 7 V-graph showing design and best observed speeds for the example jam packing line Plotting best observed speeds highlights problems that may need urgent corrective action, rather than identifying the real bottleneck in the line. A large discrepancy between design and observed speeds gives information for an individual machine much as a low value for reduced speed indicator gives information for the line as a whole, ie it suggests: mechanical problems, eg a worn-out bearing, a burnt-out motor winding or problems with the compressed air system (making cycles longer); material problems, eg off-specification product (eg the thick jam in the example) or jars that are slightly too wide and thus take longer to be forced down the feed chute. Prompt action stops engineering problems developing into catastrophic failures that could shut down the line at a high cost in lost production. Problems with materials also need to be sorted out quickly to prevent inefficiency. 19

24 5 STEP 4 - INVESTIGATE INDIVIDUAL MACHINE AVAILABILITY STEP 1 Map the process How well is your packing line designed? Monitor regularly and continue to improve. STEP 2 Calculate performance indicators Do you have a problem with your packing line? STEP 7 Take corrective action STEP 3 Investigate individual machine speed Are plant items performing to design? STEP 6 Identify root causes of problems STEP 4 Investigate individual machine availability How reliable are plant items? STEP 5 Identify key problem areas 5 This Section explains how to quantify the reliability of individual machines and plot the value on the v-graph in order to identify which machines are contributing to poor packing line performance and, hence, need attention. To do this, the availability of each machine during normal operation is taken into account. 5.1 WHAT IS MEANT BY AVAILABILITY At any given time, an individual machine can be: running at full capacity, ie at or close to its best observed speed; running below capacity, ie either running well below its best observed speed or stopped. In normal operation, a machine spends most of its time running at its full capacity but also spends some time running below capacity. Availability is a measure of the time an individual machine runs at capacity as a proportion of the time it could have run at capacity. Low availability shows that a machine is stopped or running at reduced speed for significant periods of time due to factors inherent to that machine. This may also be creating significant downtime for the line as a whole. The availability of a particular machine should not reflect stoppages due to other machines or the operation of the line as a whole. For example, it should not reflect times when, as a result of good packing line design, the control system may have stopped it to avoid blockages at the following machine (build-back time). Nor should it reflect times when it is left idling whilst waiting for feed from the preceding machine (starvation time). Availability is determined by carrying out an event study (see Section 5.3). This involves observing the machine for a specified period, recording the length of all events when the machine is running below capacity and noting their cause. The availability of an individual machine is equivalent to the downtime performance indicator for the whole line (see Section 3.2.2). 20

25 In order to represent individual machine availability in a meaningful way on the v-graph, the mean effective rate (MER) is calculated and plotted. MER = Best observed speed x Availability The completed v-graph will highlight the reasons for poor packing line performance and provide clues to possible improvements. Availability and MER highlight the effects of instances when a machine is running below capacity because of factors inherent to the machine. Such factors include: mechanical breakdown problems; blockages on the machine caused by poor handling of materials or out-of-specification materials; incorrect control signals, eg due to badly positioned sensors. 5.2 TYPES OF BELOW CAPACITY RUNNING Events when a machine is running below capacity can be divided into four important types (see Table 1). Description of event The machine stops or runs slowly: because of a failure in the supply of materials to the machine due to lack of space on the out-feed taking away product due to a problem local to the machine itself for a reason that is not known or not observed *NB Other names are sometimes used Table 1 Types of below capacity running event Type of event* Starvation time Build-back time Inherent time Unknown time 5 Assigning events to one of these categories provides pointers to the source of problems and the potential for improvement (see Table 2). Dominant type of event Main opportunity for improvement Starvation time and/or Problem probably lies upstream (for starvation time) or downstream build-back time (for build-back time) of the machine being studied. Inherent time Concentrate on improving the machine s performance, eg by improving maintenance or the quality of packing materials. Unknown time More event studies are needed to clarify the picture. Consider obtaining assistance to help identify problems as they occur. Table 2 Useful information obtained from categorising below capacity running events When assigning an event to a category, it is important to consider the effects of control systems and sensors. Otherwise, inherent problems may be missed by looking at the symptoms rather than the cause. For example, in the Industry Example in Section 5.7, the cause of an inherent problem was the position of a sensor at the coder, but the symptom was the coder being starved of product while it waited for the conveyor to move materials from the weigher. In this case, the observer made the correct choice between starvation time and inherent time because he knew from experience that the pattern of product on the conveyor was unusual. 21