Moshe BenBassat
Chairman, Plataine
It has been a good year for Global Furniture Corporation. Consumers have been wooed by new designs and ample choices of styles. The retail outlets have been happy with the quick delivery times promised by Global, and the orders kept pouring in as the holiday season was approaching.
Jim, the plant manager at Global, has been busier than ever, but he barely had time to complain, and the prospect of a fat bonus at the end of the year has been keeping him smiling through the madness of around-the-clock production.
This morning was no different, with the arrival of a substantial order from JVL; a large and frequent client. Looking at the details of the JVL order, Jim could see that it consisted of a high mix of products. Even if they start cutting today, they will barely make the required delivery date. (Jim’s CAD/CAM library contains, of course, the designs of the individual products that were ordered, and their nesting and cutting programs for the routers).
Upon further analysis, Jim realized that if they were to utilize the cutting programs as is, there will be tremendous plywood waste, which will cut deep into the margins of the deal (and eventually into Jim’s bonus…) Pondering his options, he could sense that simultaneous nesting of two or more products will yield 20% to 25% material savings; it will even shorten the overall cutting time. The problem is that re-nesting and re-programming would also take time, and his people are too busy with the new designs that have just come in for the upcoming season. “I wish I had more time to take an integrated look at the entire process, and design an optimal production plan”, Jim sighed. As he continued his struggle with today’s plan, he realizes that this has been the trend recently: high mix low volume with shorter and shorter delivery times, combined with constant pressure from the CEO and CFO to improve efficiencies and profitability.
The Optimal Production Plan
Optimized furniture production plans are aimed at balancing multiple and often conflicting objectives stemming from multiple sources: shorter delivery times, low-volume high-mix orders, ever increasing raw material cost, cheap off-shore labor, and the ultimate need for growth and profitability.
Searching for the “best” plan means that we are able to compare any two plans and judge one to be better than the other. Such an evaluation function- also known as objective function- typically combines several factors, including material utilization, cutting time, assembly time, and others. Whatever the objective function is, there are some principles that are likely to improve the outcome of the “best” plan:
Principle #1: Comprehensive, simultaneous coverage of all variables produces optimal solutions with better values. For example, while optimizing the nest for material utilization, you cannot ignore the cutting time of the tool path. The optimization process must consider both of them simultaneously.
Principle #2: Higher flexibility in mixing parts of different styles/frames and customer orders yields better value for the optimal plan. The basis for this principle is the classic “Rocks, Stones, Sand” principle. Namely, for a given plywood board, the higher the variety of parts which can be considered for placement, the higher the potential utilization. If you only have large parts to nest, the opportunity for optimizing material utilization is very limited.
Principle #3: The longer your planning horizon is, the better overall performance you can achieve. The further away you look, the more complete the information your have and the higher the number of options you can consider for optimization.
Principle #4: Continuous optimization enables overall better performance. What was optimal an hour ago may not be optimal any longer. At any given time, new information comes in: jobs take longer than planned, new high priority jobs come in, a machine may be down, etc. Being able to act in real-time and modify the plan to continually maintain optimality ensures that we squeeze the most out of the available capacity and respond in a manner which is consistent with our business priorities.
The Production Reality
The essence of producing an optimal production plan is searching for the “best” plan among a set of “legitimate” plans. The search process itself revolves around systematic and efficient exploration of various combinations. However, to come up with a production plan that can actually be executed, and is not just a theory, we must limit our search to those “legitimate” plans that are consistent with the practical business and logistic constraints of running a production floor.
A legitimate production plan is defined by a set of must and must-not rules, which may be grouped into two types. The first type of rules is dictated by technological and logistic considerations which--if violated--will yield unacceptable results. For instance, consider a rule that says “For vacuum-based cutting tables, do not nest many small parts together“. The reason for this rule is that as we cut small adjacent parts, the vacuum weakens, which may cause parts to be damaged. Such rules are inherent part of the process and do not leave much room for flexibility.
The second type of rules is self-imposed, as a result of business and operational practices. For example, rules such as “Do not mix parts from different frames” or “Product X is always cut on machine B”. It is important to understand that as the number of rules increases, the ability to optimize our plan decreases. Therefore the business implications of every rule should be carefully evaluated and revisited periodically.
Some of these rules may be relaxed with different processes or different technology and tools. Such relaxation may ultimately lead to significant improvements in the outcome of the optimal plan. For example, the use of a rolling nest offers more flexibility and hence better material utilization (See Figures 1-3 below). Relaxing a rule does not necessarily mean that it has to be totally ignored. For example, rather than the rule “Do not mix parts from different frames”, we could use a more flexible version such as “OK to mix parts of different frames, but within no more than distance X between parts of the same order”.
Optimization is Here -- Now it’s up to You!
Devising production plans that are both optimal and practical is an effort that requires a combination of process, technology, and people. Leading furniture manufacturers--such as Ethan Allan, Southern Furniture, and others--are adopting new business practices and technologies that embed the optimization concepts described here with encouraging measurable results.
When seeking new technologies to help us optimize production, we need to look for those technologies that enable new processes and paradigm shifts. Not a faster train, but one that can fly. We also need people who are willing to fly. And more than anything, we need managers and leaders that have the vision to look up and reach for these new horizons.
Figure 1: conventional nesting of four identical sofas requires four plywood sheets
Figure 2: optimized nesting of four identical sofas using rolling nests requires only three plywood sheets.
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