Assembly Line Balancing Jaime Joo MBA 530 – Section 1 Brigham Young University

Outline What is Assembly Line Balancing? How can Assembly Line Balancing benefit your operations? Classic approach to ALB Let’s practice! ALB in the real world Conclusions

What is Assembly Line Balancing (ALB)? ALB is the procedure to assign tasks to workstations so that: Precedence relationship is complied with No workstation takes more than the cycle time to complete Operational idle time is minimized By the Precedence Relationship, some tasks require one or more other tasks to be completed before starting, thereby creating an order in which tasks must be performed. Cycle Time or Workstation Cycle Time is a uniform time interval between successive produced units.

How can Assembly Line Balancing benefit your operations? A balanced line: Promotes one piece flow Avoids excessive work load in some stages (overburden) Minimizes wastes (over-processing, inventory, waiting, rework, transportation, motion) Reduces variation Promotes one piece flow: By promoting one piece flow, it is easier to implement the JIT concept and Pull-System production, favoring Lean Manufacturing Avoids overburden: promotes a healthier work and social environment Minimizes wastes: in over-processing by avoiding unnecessary work in stages previous to bottlenecks, in inventory by avoiding accumulated pieces before the bottleneck workstation, in waiting time by minimizing idle time in every workstation, in rework by reducing over loaded workstations thereby reducing the probabilities of failure, in transportation and motion by reducing over accumulated work-in-process inventory Reduces variation: smoothing the process, also implies smoothing variation.

Unbalanced Line !?  Zzz Zzz 10 sec 40 sec! 20 sec 15 sec Overproduction! Generates waste Undesirable waiting

Balanced Line     25 sec 25 sec 20 sec 15 sec Promotes one piece flow Avoids overburden Minimizes wastes Reduces variation

Line Balancing prerequisites Prior to balancing a line we must: Determine the required workstation cycle time (or TAKT time), matching the pace of the manufacturing process to customer demand Standardize the process Sometimes these prerequisites constitute serious impediments to implement balanced assembly lines when there is not a good understanding of the market or customers or when the process is not easily standardize able (i.e. highly customized products).

Classic approach to ALB Also known as SALBP* (Simple Assembly Line Balancing Problem), the classic approach to ALB is an heuristic process to optimize assembly lines simplifying the problem to a basic level of complexity Heuristic: “…a method for helping in the solving of a problem, commonly informal. It is particularly used for a method that often rapidly leads to a solution that is usually reasonably close to the best possible answer. Heuristics are rules of thumb, educated guesses, intuitive judgments or simply common sense. In more precise terms, heuristics stand for strategies using readily accessible though loosely applicable information to control problem-solving in human beings and machines.” (Wikipedia) SALBP only considers two constraints, precedence and cycle time. As we will see, even when this approach is generally valid, it ignores other important aspects present in real assembly lines. *Dubbed SALBP by Becker and Scholl (2004)

Example The next table shows the tasks performed in a production line. Our goal is to combine them into workstations. The assembly line operates 8 hours per day and the expected customer demand is 1000 units per day. Balance the line and calculate the efficiency and theoretical minimum number of workstations.

Example (cont.) Task Task Time (sec) Preceding Task A 13 - B 11 C 15 D 20 E 12 F G H 18 D, E I 17 F, G J H, I K 9 Total Time: 156

Example (cont.) 20 sec 11 sec D 18 sec B 12 sec H 13 sec E 15 sec Step 1: Draw a precedence diagram according to the given sequential relationship 20 sec 11 sec D 18 sec B 12 sec H 13 sec E 15 sec 9 sec A J K 13 sec 15 sec F 17 sec I C 13 sec G

Example (cont.) Step 2: Determine Takt time or Workstation Cycle Time C=Production time per day / Customer demand (or output per day) C= 28800 sec (8 hours) / 1000 units = 28.8 Step 3: Determine the theoretical number of workstations required N= Total Task Time / Takt time N= 156 / 28.8 = 5.42 (~6 workstations) Step 2: Production time per must be expressed in seconds since Task times are in seconds Step 3: The result is rounded up. This is just a theoretical number, the actual number may be greater

Example (cont.) Step 4: Define your assignment rules. For this example our primary rule will be “number of following tasks” and the secondary rule will be “longest operation time” It has been demonstrated that these rules effectively limit the balance achievable, however assigning priorities for these rules depends on the problem structure.

Example (cont.) 11 sec 13 sec B Following tasks: 5 A Lot: 15>11! Step 5: Assign tasks to workstations following the assignment rules and meeting precedence and cycle time requirements To form Workstation 1: 11 sec 13 sec B Following tasks: 5 To meet precedence requirement obviously we start with task A (13 seconds) As we have not met the cycle time constraint, there is room for another task, the next feasible tasks, since task A is already considered, would be B and C Our primary rule is “number of following tasks”, the same for both, let’s move to the secondary rule The secondary rule is “longest operation task” or LOT, C task time is 15 seconds, B task time is 13 seconds, we choose C. We have reached 28 seconds (13+15), it is not possible to add any additional task without violating the cycle time, we close the workstation with A and C A Lot: 15>11! 15 sec C Following tasks: 5 WS1: A+C=28 sec Cycle Time met!

Example (cont.) G 13 sec F E 12 sec D 20 sec B+D>Cycle time! 11 sec Forming Workstation 2: G 13 sec F E 12 sec D 20 sec B+D>Cycle time! 11 sec 13 sec B LOT:_F&G>E A 15 sec We start with B, since in this moment it is the task with the most number of following tasks (5) Our next alternatives are D, E, F or G, all of them with 3 tasks following (primary rule) D is not considered because the workstation would exceed the cycle time Following the secondary rule, we discard E because F and G have longer operation time Between F and G, both with 13 seconds, we arbitrarily choose F The second workstation is completed with 24 seconds of operation time C WS2: Operation time=24 sec (<C) Arbitrarily choose F

Example (cont.) Following the same criteria we achieve our balancing with 7 workstations

Example (cont.) How to interpret this efficiency? Step 6: Calculate Efficiency Efficiency= Total Task Time / (Actual number of workstations * Takt Time) Efficiency= 156 / (7*28.8) = 77% How to interpret this efficiency? Is this the best efficiency achievable? An efficiency of 77% should be interpreted as 23% of imbalance or idle time across the line. There are 45.6 seconds of total idle time, the lesser the total idle time, the better the efficiency of our balanced line. In some cases, changing the priorities in rules can lead to better efficiency.

Let’s Practice We have found a new market for our product. This market is less demanding so we have decided not to include a particular feature, specifically the feature added by task I. As a consequence, task time in F drops to 5 seconds and task time in G drops to 8 seconds. Balance the line according to the other conditions.

Let’s practice (cont.) Task Task Time (sec) Preceding Task A 13 - B 11 15 D 20 E 12 F 13 5 G 13 8 H 18 D, E I 17 F, G J (new I) H, F, G K (new J) 9 Total Time: 156 126

Let’s practice (cont.) Let’s take some time to solve this new problem. This time we will calculate keeping the primary and secondary rules as in the original problem.

Let’s practice (solution) Precedence diagram 20 sec 11 sec D 18 sec B 12 sec H 13 sec E 15 sec 9 sec A I* J* 5 sec 15 sec F C 8 sec *Previously J & K respectively G

Let’s practice (solution) Takt time C = 28,800 sec / 1000 units = 28.8 Theoretical number of workstations N = 126/28.8 = 4.38 (~5 workstations) Primary rule: number of following tasks Secondary rule: longest operation time

Let’s practice (solution) Following the rules and observing cycle time and precedence we obtain:

Let’s practice (solution) Efficiency = 126/(6*28.8) = 73% Challenge: Is this the best efficiency achievable? Try to solve with LOT as the primary rule and you will obtain a 5 workstations balance, increasing efficiency to 87%

ALB in the real world The simple ALB problem approach is limited by some constraints: Balance on existing and operating lines Workstations have spatial constraints Some workstations cannot be eliminated Need to smooth workload among workstations Multiple operators per workstation Different paces among operators, different lead times within the same workstation Balance on Existing and Operating Lines: Most of the time, the procedure will be implemented over existing lines, for different reasons (increasing capacity, introducing new technology, etc.) Workstations spatial constraints: For example, a workstation located in a place with reduced vertical space won’t be able to perform tasks where lifting of the product is needed Workstations cannot be eliminated: Some operations can only be assigned to certain workstations, some workstations cannot be eliminated without creating physical gaps in the process Need to equalize loads: If some workstations cannot be eliminated, the aim of the optimization should be to smooth the workload among existing workstations. Minimizing the cycle time per workstation is only necessary when it exceeds the target, when the required cycle time is met, the task of smoothing the work load should be aimed. Multiple operators per workstation The assigned time to a specific workstation with multiple operators should be equal to the time required by the slowest operator

ALB in the real world (cont.) Operator spatial constraints Different workstation imposed working positions More than one task to be performed in what should be the space for one task Multiple Products Coping with different products, some operations are needed for some products but not for others Some products can introduce “peak times” in some workstations Different task times performed in different shifts Particularly when introducing new employees or workers with some degree of incapacity Operator spatial constraints: Some workstations need the product to be in a particular spatial position limiting the operations to be performed to the available working space (for example, if the product right side is close to a wall, operators will only be able to work on the left side of the product) If more than one task should be performed on the same spot, special scheduling is needed within the workstation, or the tasks on the particular spot should be assigned to only one operator (to avoid clashes among operators) Multiple Products If operations of a specific workstation are needed in some products but not in others, to obtain the most accurate average lead time in this workstation, the lead times should be calculated independently for each product, and then averaged according to the product percentage. Infrequent products could introduce peak times, these peak times must be taken into account for each workstation, usually, considering only the average process impedes an accurate perception of these peaks. To keep the peaks at reasonable levels is critical. Different task times performed in different shifts If there is an unskilled employee or handicapped employee in a particular shift, the slower pace could make it difficult to meet the required times for our balancing plan

Conclusion Simply Assembly Line Balancing is a valid method to optimize assembly lines. However, many variables found in real operating lines increase the complexity of the problem. More complex algorithms have been developed to solve the difficult task of balancing large scale industrial lines. Some of them are commercially available in software.

References F. Robert Jacobs & Richard B. Chase “Operations and Supply Management, The Core” McGraw-Hill/Irwin First Edition Emanuel Falkenauer “Line Balancing in the real world” Optimal Design Paul Swift. http://www.beyondlean.com/line-balancing.html