Part 1 of this blog series started with the fact that the ability to sense demand and become a demand-driven (responsive) business is more than just the catch phrase du jour: it has become a recipe for survival. Every sensible enterprise is on a quest to deliver on time and as quickly as necessary, with minimum inventory (and working capital), and the highest necessary utilization.
For a few decades, the providers of a multiplicity of by and large integrated manufacturing software solutions have been offering help for embattled manufacturers. From fully integrated business management systems such as Enterprise Resource Planning (ERP) down to more focused modular plant-level solutions including Manufacturing Execution Systems (MES), and Advanced Planning and Scheduling (APS) systems, manufacturers have been perplexed with how best to combine and deploy these options and islands of information.
The article concluded that ERP systems are good for planning and transactional accounting purposes, but not necessarily appropriate for scheduling and execution on the shop floor. Only those companies that have infinite (or lots of spare) capacity, low product mix, their customers’ tolerance for long order lead times, and low inventory holding costs could get by using ERP for scheduling.
In other words, not many manufacturers can be fully satisfied by ERP. The next logical question is whether Lean Manufacturing practices can alleviate the abovementioned ERP shortfalls.
As said in Part 1, lean thinking revolves around the concepts of takt time (production rate or drumbeat), heijunka (load leveling and line balancing), and manufacturing process redesign to make it more agile (i.e., the ability to quickly change between product runs and reduce setups). In such a setup, a Visual Production Control (VPC) that uses common sense visual signals (i.e., Kanbans or supermarkets) to initiate (trigger) a new action (e.g., replenish an empty container or bin) should suffice, right?
Not really. Even though lean manufacturing initiatives are putting the focus on reducing cycle times and changeover times, is VPC necessarily the optimal technique? As a nitpicking example, say, if a lean manufacturing company stopped accepting orders tomorrow and then waited until its VPC-run factory to stop, how much inventory would it have left? Well, the kanbans will be full, which is still less work in progress (WIP) than in non-lean plants, but the company is still not the leanest.
Lean: Not the Panacea for Customized Items and Variable Demand
Although lean initiatives that include “pull” signal systems seemed to be the way to go but for many manufacturing environments, kanban systems as a way to control production only go part of the way to completely satisfy a make-to-order (MTO) environment. Dedicated resources in manufacturing cells, which kanban systems tend to force to accommodate the group technology (GT) design, rarely provide the agility and flexibility companies need in case of variable demand and a changing product mix.
Along similar lines, lean is often based on the concept of Period Batch Control (PBC) with its fixed sequences to also accommodate GT items, which also reduces flexibility. Again, variable demand and a changing product mix can play havoc with even the most carefully planned lean (yet rigid) production lines.
With VPC, scheduling decisions are based on empty kanbans in isolated cells, rather than on company wide key performance indicators (KPIs), such as overall delivery performance and cost. With VPC only, the planner cannot obtain the whole picture – i.e., his/her decision-making cannot take all issues into account to allow tradeoffs between critical KPIs (and “what if” scenarios to be tested).
In fact, many lean deployments are so focused on removing waste that lean has become a synonym for cost cutting, often at the expense of manufacturing responsiveness and having adverse consequences on customer service levels. Indeed, what about the so-called “repeaters” and “strangers” (in Preactor’s lingo), the products that entail the remaining 94 percent of the product range and that by definition have variable demand? As said in Part 1, the so-called “runners” that lean manufacturing is well suited for comprise only about 6 percent of products and 50 percent of revenues.
Ironically, these more customized products will likely have higher profit margins than the runners and they may contribute to more than half of the company’s revenue and profit. If a company has dedicated resources to its runners, how does it cope with (likely profitable) surges in demand for repeaters and strangers? Dedicated cell systems can be inefficient due to product mix and the effects of the every product every interval (EPEI) sequences and changeovers. TEC Blog’s recent opinion poll has a number of valuable and insightful comments by readers.
Scheduling Comes to the Rescue
Scheduling has long been an overlooked critical competency. It has fallen through the cracks between ERP systems (that make fundamentally flawed infinite capacity assumptions) on one side and MES tools on the other side. Namely, MES solutions cannot affect the realities of having (or not) enough materials and capacity to deliver products on time and are largely unable to optimize schedules and do model WIP inventory levels.
How is scheduling different from planning, and why is the planning-scheduling tandem important? Well, planning systems work in future time buckets (monthly, weekly, daily) and cannot preserve the planned operation sequences (or respond with adequate changes) within the time bucket, once the actual production starts.
Conversely, true scheduling systems are bucketless, can preserve sequencing optimization (based on efficiency goals, profit objectives, customer service, and other key business drivers), and are capable of generating updated work-to or dispatch lists. Scheduling tools execute the resource planning process, taking into account capacity, labor, and material constraints.
Resources are scheduled to eliminate waste by reducing set-up times, bottlenecks, idle capacity, WIP, expediting costs, etc. Collaborative scheduling tools allow planners to relatively quickly respond to disruptions on the shop floor and immediately assess the impact by looking at specific strategic metrics. Namely, optimization rules enable planners to schedule with multiple objectives in mind, including desired customer service levels, operational efficiencies, cost containment, and profit objectives.
These tools allow enterprises to standardize the planning process and align departmental goals. Assignment of operation to resource is a key function to achieve operational efficiency and optimizing performance. The typical results are more on-time deliveries, increased customer satisfaction, lower costs, increased efficiency, and increased visibility across departments. In a multi-facility planning environment, APS solutions can span multiple plants and determine which plant can provide the fastest service.
APS as Manufacturing Enterprise Glue?
At long last, these days APS is finally being recognized for what it is – a key enabler for many manufacturing companies in becoming more agile, responsive, and efficient in dealing with variations in demand. According to Preactor, there are still some lingering myths about APS, but some vindication has been coming to these long maligned solutions.
Many of us might remember the late 1990’s when APS was hyped as a tool that would be a key enabler for most manufacturing companies in becoming more responsive and efficient in dealing with variations in demand and with unplanned disturbances on the shop floor (and in the entire supply chain, if you will)? TEC’s 1999 article entitled “Advanced Planning & Scheduling: A Critical Part of Customer Fulfilment” still seems timely today even after all these years.
A number of APS providers cropped up at that time, some of which were once high-flying companies with salad days of high initial public offering (IPO) valuations and thriving stocks. Many of them have meanwhile ceased to exist as independent entities, such as i2 Technologies, Manugistics, Numetrix, SynQuest, RSS Scheduling, Fygir, etc. The others, such as Adexa, Asprova, Ortems, Preactor, Taylor Scheduling, AspenTech, Logility, Demand Solutions, Planetogether, WAM Systems, etc. have been doing fine, by end large. Even the abovementioned former companies and their value propositions seem to have lately been reborn within their new parent companies, who include JDA Software, Oracle, SAP, and Infor.
Why did many of those best-of-breed APS companies fail in their first market attempt? Well, for many reasons, starting with mismanagement and the SAP APO and Oracle APS newcomer products “eating their lunch” in many instances.
Another major reason was their focus on long-term demand planning and predicting what might happen on the far horizon. Not only were these planning methods and algorithms too complex and arcane for regular users to deploy, but these systems were also then largely unresponsive, i.e., unable to schedule in near real-time, let alone accommodate unplanned events such as asset failures, manufacturing nonconformance runs (scrap, rework, etc.), engineering change orders (ECO), and rush jobs (for very important customers).
In other words, companies had little use for these APS systems’ sophisticated “what if” capabilities in terms of varied demand and forecast simulations over future months and years, since they could not address the short-term firefighting realities of the shop floor execution. Lately, though, these products have seen a renewed interest due to their native scheduling capabilities, integration to ERP and MES products and due to the general public’s recent realization of the value that demand planning has in the realm of strategic integrated business planning (IBP) and sales & operations planning (S&OP).
For more information, see TEC’s 2009 series entitled “APICS 2009 From the Expo Floor: Is S&OP Coming of Age?” Contrary to APS use in manufacturing, field service scheduling systems have always fared well, as seen in my recent series entitled “The Magic Behind Planning and Executing Optimal Service Supply Chains.”
In fact, similar principles of scheduling and optimization have lately been used in workforce scheduling products too. For example, if companies can see that they are not scheduling much for finished goods, or that they are not expecting many goods coming in, they do not need to run their retail stores or warehouses overtime. They can change their working shift patterns and use their annualized hours scheme better. For more information, see my recent series entitled “Integrated Workforce Management (WFM) Platforms: Fact or Fiction.”
The final part of this series will analyze how APS relates to ERP, lean manufacturing, and MES. In the meantime, please send us your comments, opinions, etc. We would certainly be interested in your experiences with these software categories and your best practices.