The digital design of products and production systems - the so-called Digital Factory - comprises a network of digital models and methods for
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3 The digital design of products and production systems - the so-called Digital Factory - comprises a network of digital models and methods for computer-supported modelling, simulation and visualization. The goal is the integrated planning, implementation, management and continuous improvement in all major production processes (VDI guideline 3633, Sheet 8, 2005). The informative value of Digital Factory models is significantly affected by time structure and time data of the modeled work processes. For a realistic representation of assembly operations it is, for instance, necessary to consider the variability of human performance and limited human reliability. For example, a probability density function can be used in the model to represent the time-on-task and a discrete type random variable to represent unpredictable iterations due to human error.
4 Different operational applications of time data can be distinguished independently from the respective area of operation. In an industrial context, a product-, a production, a personnel-related and a management relevant application area can be differentiated and lead to four essential application areas of time data. In order to achieve a favorable relation of the data acquisition and calculation costs to the benefits of the time data, bottlenecks in term of productivity and capacity should be put into focus. Also, the time data should be used to make rational and humane scheduling decisions.
5 Procedures and processes can be classified according to working persons, work equipment, operational resources, and work objects. With help of these systematics, nonproductive elements of processes can be identified. The classifications according to working person and work equipment correspond to each other.
6 The starting and ending time during the execution of tasks can be subject to statistical effects, such as personal factors (qualification, skills etc.) or environmental factors (temperature, lighting, noise, etc.). The resulting variance of execution time can be modelled by an appropriate confidence interval a predefined fraction of the probability mass around the mean (typically 95% or 99%).
7 The outline of process types for the work object encompasses all events that can occur for a specific order during one or more shifts within one business accounting period (month, quarter, year), from the arrival into the company (receipt of goods) to the departure (shipping) from the company. Just as for the process types for humans and work equipment, the process outline for the work object does not only take into account events that occur during the interaction between humans and work equipment, but also considers recumbency and storing. The process of modifying, checking/repairing, recumbency and storing work objects from their arrival until their departure from the company can also be referred to as flow or material flow. (REFA: Methodenlehre der Betriebsorganisation. Datenermittlung, 1997)
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9 The process outline for work equipment and related production facilities includes not only purely technical processes but also events that occur during the interaction between human and machine for the completion of a work task. It also includes events and their causes that occur outside of human-machine interaction, such as damages to the equipment. (REFA: Methodenlehre der Betriebsorganisation. Datenermittlung, 1997)
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11 The outline of process types for humans encompasses all individual activities that could occur as long as the person is at the disposal of the company in terms of work or business relationships and the labor law, including legally and contractually regulated breaks.
12 There are essentially four causes for an additional activity: 1. organizational and technical disturbances in the workflow 2. voluntary or assigned assistance from other persons 3. lack of information 4. activities without a special order
13 As shown in the previous lecture, the processes of a work system are decomposed into discrete activities; these activities can be assigned to the above mentioned process types. Beside the level on duty, the levels plant closed (example: short-time work) and off duty (example: illness, accident, vacation) continue to be taken into consideration in this outline of processes and procedures.
14 This example shows an outline of processes and procedures for the simple task drill a hole into the work piece using a drill press.
15 - A primary activity is a scheduled, immediate activity for the fulfillment of the work task. - A secondary activity is a scheduled, indirect activity through which the work task is fulfilled. - An additional activity is dealt with when its occurrences or process cannot be predetermined. - Causes of an additional activity: - organizational and technical disturbances in the workflow (additional activity = remedying of disturbance) - voluntary or assigned help by other persons lack of information (example: drawing is missing; additional activity = acquiring the information) - activities without a particular order (e.g.: cleaning task, business discussion) - The interruption due to the cycle is a scheduled waiting by the person for the end of the cycle sections that independently occur for the work equipment or work object (work equipment or work object is time determining; e.g., heating of an injection molding tool). -The interruption due to dysfunction of the task is the additional waiting by the person due to technical and organizational disruptions and a lack of information. The cause for the interruption is remedied through other persons. - Recovery is the interruption of the task in order to reduce the work fatigue accrued during the course of the task (example: relaxing after smithery, relaxing after monotonous controlling tasks). - Interruption due to personal reasons occurs when a person interrupts a task for personal reasons (example.: lavatory use, cigarette breaks).
16 Predetermined times are common for humans and work equipment. The planned time for humans is called work order time (T), and for work equipment it is called holding time (TB). Work order times, according to REFA, are actual times for workflows carried out by humans and work equipment. The work order times for humans contain basic times, recovery times and additional times. Two types of allowed times are distinguished: 1. Order-dependent times: These times refer to a concrete order with a certain lot size which has to be produced. 2. Order-independent times: These times refer to a certain quantity unit (e.g., 1, 100, or 1000 items).
17 Due to the differences in actual and target times, it is necessary to clarify the causes and to redesign the work process. There are different methods for time calculation. Experimental procedures serve for the calculation of actual times. Computational methods like predetermined motion-time systems are the basis for the calculation of target times. (Schlick et al.: Arbeitswissenschaft. Springer Verlag: Berlin, 2010)
18 The procedure is dependent on the acquired data s intended use. The intended use determines the scope of the time recording and its level of precision.
19 Central to time recording is the observed actual work process. The result of the observation is recorded with help of a time measurement device (e.g., stop watch) and a time observation sheet. It is important that the time recording is reproducible according to the information on the time observation sheet. The accompanying circumstances must be captured as carefully as the times themselves. Step 1: Concerning the purpose it has to be determined whether the time study should be used to develop company time standards or determine only planned rimes for specific work systems. Step 2: Within the framework of the preparation, it is for example necessary to ensure that those employees are informed, who are effected by the time study.
20 Step 6: This step serves the reproducibility of the time study.
21 For flyback timing, each operational procedure sequence is measured individually, i.e., the watch hand is stopped after every reading and restored to the initial position. The measured individual time t i then represents the duration of a process section. Advantages: no calculation of individual times necessary, dispersion of measured values identifiable immediately. For progress time measurement the time measurement device is activated at the start of the time recording and runs during the entire recording period. The progress time is read for the corresponding measurement points. The individual times t i must then be calculated from the progress times. Advantages: gap-free time measurement; reading errors are counterbalanced in the following time measurement period.
22 Performance rate: The performance delivery and thereby also the time requirement for the execution of work are, even with constant work conditions, subject to temporal fluctuations. Measured actual times must therefore be re-calculated as target times. This occurs with the help of the performance rate, which is evaluated parallel to the time measurement. The observed actual performance is thus evaluated in relation to a reference performance. In order to obtain the target times, the acquired actual times are multiplied by the estimated performance rate. If the observed performance conforms with the expectations in terms of intensity and effectiveness, the performance rate is set to 1 and the actual times correspond to the target times. If the observed performance is lower than the performance which can be expected from the majority of workers, a performance rate lower than 1 is assigned
23 A work sampling study provides a good reflection of the actual state in a work system with relatively little effort. The results can also be determined to every desired degree of precision through an increase in the number of notations (sample size). During one round tour, as many workplaces as desired can be observed. L.H.C. Tippett, statistician at the Shirley Institute of the British Cotton Industry Research Association in Didsbury, is generally identified as the mastermind of the work sampling method. Since 1927 he occupied himself with his Snap-reading-method of making time studies, which was not published until 1934, thereby laying the foundation for the future work sampling method. Tippett investigated the downtimes in a weaving mill, for example. (...) An observer went from machine group to machine group and observed the activity of the workers at each for a moment. Thus, thousands of observations were recorded and then mathematically evaluated. Result: With a continuous increase in the number of observations, the confidence interval of the recordings of the relative frequency of a work activity inevitably includes the true value. (Haller-Wedel, E.: Das Multimoment-Verfahren in Theorie und Praxis. München 1969, S. 20 f.)
24 - REFA has developed a standard program for the execution of the work sampling study - There is a difference between the work sampling frequency (MMH) and the work sampling by methods of time-on-task measurement (MMZ). - Both methods are based on qualitative discrete features (counted measurands). While the work sampling frequency (MMH) only allows a conclusion concerning the relative frequency of a certain feature within a sample, the work sampling by methods of timeon-task measurement (MMZ) additionally allows to draw a conclusion concerning the duration of a certain activity. - In practice the MMH is used the most. - MMH: In its simplest form, the procedure is performed in such a way that the observer makes a tour past the workplaces in a particular cycle, thereby noting on a tally sheet which activity is being conducted by which worker at the time of observation. The observations must be representative, since only a relatively small number of tours occurs. - MMZ: Both methods have in common that they are sampling procedures. The MMH data provides information concerning the relative frequency of observed activities, while the MMZ method provides estimates of time values. Approach: The observer makes annotations at irregular points in time. In doing so, the type of executed work, as well as the exact point in time of the observation must be noted. Based on these notations, it is possible, for example, to identify the last notation before operational procedure B, the first and last notation within the operational procedure B, and the first notation after the operational procedure B from the total notations per operational procedure. With the help of these times it is possible to calculate a minimum and a maximum duration for the operational procedure B and to estimate the mean and standard deviation of the
25 execution time. (Kaminsky, G.: Praktikum der Arbeitswissenschaft. 2. Aufl. 1979, p. 298ff., 310ff.)
26 The generally accepted principle of a work sampling study is illustrated by the comparison of a typical complete time measurement to a MMH recording and evaluation with use of a time-bar model. During an eight hour workday - shown by a horizontal time bar comparable yet completely irregular activities (e.g., repair work) are performed with corresponding time types t 1 (e.g., primary times), t 2 (e.g., secondary times), t 3 (e.g., additional times) at 5 workplaces. For the usual measurement method of time lengths through time recordings, e.g., with help of a stop watch, the percentage proportions of the three time types at shift time T and the average for the total department are listed on the right side. It then becomes clear that the method of work sampling based on (relative) frequencies is much more effective than the collection of times-on-task via stop watch.
27 1. Sample: The observed and noted characteristics, procedures or events in the statistical sense (time types, workplaces, persons, work equipment, work pieces, parameters, etc.) during a tour make up a sample. The role of statistics is to make an inference from the sample to the total population. 2. Homogeneous: The sample must be taken from a uniformly structured population. This means that two different populations at the same time, i.e. mixed with each other, cannot be taken on at the same time (e.g., work equipment efficiency studies in preproduction and assembly work areas). Mixed collectives occur when two inhomogeneous populations are observed with each other and are consolidated (e.g., in a business there are often significant differences between events in the day shift and those of a night shift). 3. Multiple: For each tour a momentary cross-section of activities of the observed work group is notated. Through repetition of these tours the cross-sections increasingly move toward specific boundary values. 4. Irregular: The irregularity of the observations/notations allow every possible event to have a calculable chance at being collected during a tour. 5. Size: The size of this sample must be sufficient by large. 6. Same coverage: An equal amount of workplaces should be observed for each tour. 7. Free choice: From a set series of possible cases (e.g., previously set outline of the procedure) the event that is notated is left to chance. 8. Without repetition : Each event is live at the moment of observation, yet becomes an irrevocable part of the past after the notation. (Haller-Wedel, E.: Das Multimoment-Verfahren in Theorie und Praxis. München 1969)
28 The interaction of humans, work equipment and material in the workplace is a lively process of interconnected and unavoidable processes and random interruptions. Since the statistical fundamentals of the work sampling procedure only permit the collection of individual processes that are independent of one another, the question of what should be paid attention to in borderline cases, which can occur in daily practice, is justified. 1. The objective dependence on events: Seen from the observation object, it can occur that a random event can initiate a chain of legitimate processes, i.e. that a cause latently allows several effects. There is a risk that, rather than the random event being observed, it is actually the numerous effects that are observed and noted instead; this leads to a biasing of the recorded fact, and thereby to an incorrect analysis of the results. 2. The subjective dependence on events: The probability that a specific random procedure is captured directly after an instance of observation in the same way greatly varies. For example, it is unlikely that a manager repeats an already given instruction directly after the observation (note: with an increase in time intervals for this event the probability of repetition increases). The subjective dependency benefits from extremely short touring intervals. Therefore, these should be avoided. 3. The dependence on events through regular touring intervals: If tours are performed in regular time intervals, the fundamental rule for drawing a sample that individual points in time of the observed event are independent no longer possess the same probability of being noted in such a controlled tour. Modeling attempts can prove these dependencies on events with certainty, especially for small touring intervals. Bias occurs when particular multiples of intervals between the tours
29 coincide with organizational regulations (e.g., break regulations), work periods or manufacturing times. (Haller-Wedel, E.: Das Multimoment-Verfahren in Theorie und Praxis. München 1969)
30 The processes to be observed must always be part of a large, as stable as possible, statistical population (e.g.: the additional times of the worker in a mechanics workshop during the recording month should be a sample of that population of additional times of workers from the same workshop since and as long as the time determining manufacturing processes exist). In order for the determined characteristics of the observed individual processes to be considered normally distributed in the limit n, they must occur in a sufficient accumulation and must also be observed independently from each other (e.g., the characteristics for objective and personal additional times). The link of the sampling procedure to the significance of the normal distribution gives the work sampling method superiority over other work study procedures and methods and justifies the reputation of the reliability of its findings. There are occasional cases in practice in which a different distribution, not a normal distribution, must be consulted. In these cases, statements about the precision and the results of a work study recording must undergo an evaluation and, if necessary, a correction. Hereby, the following instructions could possibly be useful: a low number of observations of frequencies will be binomially distributed; a greater amount will be normally distributed. Actual execution times are often lognormally distributed, while down times and wait times often follow an exponential distribution. According to unanimous expert opinion, a statistical confidence level of 95% is both sufficient and necessary for most investigations in industrial engineering, i.e., the theoretical possibility of one error within 20 results is seen as acceptable. (Haller-Wedel, E.: Das Multimoment-Verfahren in Theorie und Praxis. München 1969)
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37 For the entire MMH recording, and under the condition of the true activity proportion θ, the MMH formula from the positive and negative tails of a bell-shaped distribution can be used to calculate the upper and lower confidence limits f max and f min. The sketched-in curve shows that the estimated portion θ continuously comes closer to the true proportion θ with an increase in the sum of all notations n. (Haller-Wedel, E.: Das Multimoment-Verfahren in Theorie und Praxis. München 1969)
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