Global competitiveness is placing tremendous pressure on cost, quality and responsiveness in manufacturing. Increasing emphasis on output from distant sites hampers management visibility and control. A premium is put on asset efficiency but effective comparative measures are difficult to achieve. Plants use copies of master data, creating compliance and quality issues. Production personnel lack the decision support information to meet their targets. The business and financial impacts of production asset exceptions can’t be monitored or controlled at the enterprise level. Resources — money, people and time — are stretched thinner and thinner.
If you face any of these issues, you should take a look at integrating product and operational management into your environment. With such integration, you have visibility into all aspects of your manufacturing operations (Figure 1).
Figure 1. Effective plant-to-business integration enables faster response and better use of assets.
This provides the ability to respond faster and minimize impact to the business and bottom line, driving increased yields, asset utilization and order fulfillment — in other words, you’ve got the "perfect plant."
The perfect plant
Such a facility must excel in three essential areas (Figure 2):
Figure 2. Success requires aligning asset utilization, operations planning and manufacturing execution.
Asset performance and utilization. Assets are monitored so that events of concern automatically get visibility. Enterprise Asset Management (EAM) processes are optimized and details about all assets are available in a single source. EAM processes are tightly linked to manufacturing processes. Asset performance and utilization has moved from traditional preventive maintenance to a collaborative model.
Manufacturing execution. This is so effective that it’s nearly event-free due to proactive monitoring and automated event handling that’s tightly coupled with EAM and the enterprise. Here you have visibility across all critical processes that contribute to success of manufacturing execution. The reach of your Enterprise Resource Planning (ERP) system extends to the shop floor, accelerating operational efficiencies while at the same time ensuring safe and compliant operations.
Operational scheduling/planning. Changes aren’t primarily driven by unplanned events in manufacturing but rather by demand shifts and other factors. Manufacturing is able to manage and react more rapidly and reliably to these changes. This allows for the optimization of existing manufacturing assets and processes to reduce waste and variability. The integration of the plant with the extended enterprise and supply chain increases responsiveness to any changes.
The perfect plant aligns and improves key performance indicators and so offers significant benefits in a number of areas:
- decreased manufacturing/raw materials costs (5% is typical) through process monitoring and increased visibility;
- increased plant efficiencies (25%) via optimization of manufacturing processes and integration with the enterprise;
- higher production yields (10%) by proactive monitoring of manufacturing events;
- lower maintenance costs (10%) due to more effective practices, and alignment with manufacturing metrics;
- reduced capital investments (10%) because of better asset availability;
- smaller inventory (10%) through more efficient and consistent operations; and
- enhanced value chain agility and customer responsiveness thanks to complete value chain integration and visibility.
The first step in your quest is to decide on the elements that make up your perfect plant — such as better quality analysis, enhanced maintenance strategies that ensure better uptime, shop-floor visualization capabilities, more effective procurement, etc.
Once you can "see" your perfect plant, you can start prioritizing the individual items based on their benefits and then begin implementing those items piece by piece.
However, the devil is in the details. The following four cases illustrate some pitfalls.
Everyone believes (and they’re usually correct) that inventory levels are too high. One of the prime causes is incorrect data in the planning process. Everyone calls accurate inventory counts or the master schedule crucial. Yes, they’re important; and don’t believe that just anyone can count inventory. Other, more fundamental areas can cause significant errors that impact the inventory levels, though. For instance, don’t assume that the bills of materials or recipes are correct.
It’s amazing how many people can compare a bill of materials/recipe report to the original and miss errors. My favorite errors are around decimals; 10.0 looks a lot like 100 after a number of hours in front of a terminal. Then, there’s getting the conversion factor the wrong way around. However, even if the bill of materials exactly matches the specification, things can go wrong.
In one facility, we consistently had too much material in inventory at period end. When we showed the operators a computer generated pick list for the product and asked them what they thought the problem was, they told us that if they ever used the listed quantities of materials the product would be too thick to flow through the pipes.
As this highlights, what’s reviewed, audited and approved by management and supervisory staff isn’t necessarily what happens on the shop floor. So, do a reality check. The best way I’ve found is to generate a bill of materials’ explosion for normal production batch quantities. Then give the list to the operators who pick and move the material and who therefore have a good idea of what really is normal, and ask them if it makes sense.
Production blind spots
At another site (and typical of many others), management didn’t have visibility onto the shop floor and couldn’t reliably say what amount was being produced at any stage in the process. As we analyzed the requirements to provide such visibility, we realized that we had a worse problem than we thought. Not only could we not see what was produced, we couldn’t even get the data to visualize. Some of the counters didn’t detect product, flow meters with low volumes of material going through didn’t register any activity, and lots of equipment had no sensors or counters attached.
Visualization dashboards are only as good as the data available. To collect all the data that are needed may require investment in equipment.
Becoming aware of significant excess capacity at a facility or, more correctly, inefficient use of the capacity, we decided to see what could be done to increase asset utilization. The plant’s Industrial Engineering Department was the custodian of all the documentation and information concerning the equipment. While these details were correct (the department, after all, controlled all engineering projects and upgrades), it soon became apparent that we didn’t have enough data. Modern integrated capacity-planning systems require more sophisticated data than the information that was being collected. This was very obvious for some of the vintage equipment, which had been installed around fifty years ago and for which we could get only extremely basic information.
Once we had identified the data that the system required, we initiated a shop floor review. Engineers performed studies on how the equipment was running to gather the performance metrics needed. At the same time, we compared the physical plant to the engineering drawings. We were considering implementation of an EAM system in the future and knew it required the physical location of the equipment for scheduling maintenance rounds effectively.
The results were quite interesting. We had equipment on the drawings that hadn’t been there in 20 years, equipment in place that hadn’t made it to the drawings, pipes that went through walls that didn’t actually exist, and many nooks and crannies that didn’t appear in the plans. Of course, we also were missing documents for existing equipment but had documents for obsolete and retired equipment. Overall, it took the engineering group about one year to complete and update the physical layout plan and to update its own document database with the current as-built/as-modified and performance characteristics. Once we had the performance characteristics we then could perform capacity planning and analysis, which is why we had started the project. And, yes, we did see significant improvement in production throughput once we were able to integrate the production schedule with the capacity information.
The human element
A plant markedly lagged most of its peers in equipment uptime but spent more on maintenance. Its maintenance strategy focused mostly on emergency repair. What little maintenance that was scheduled tended to take place on the weekends because all the skilled trades were busy with emergency repair during normal working hours.
We addressed this problem by implementing an integrated EAM system. We started simply — just scheduling preventive maintenance and, more importantly, doing that maintenance on schedule. By knowing what equipment wasn’t being used, if preventive maintenance hadn’t been done, and which trades weren’t currently assigned to a task, we were able to send the trades people to perform preventive maintenance on the equipment, thus reducing the likelihood of it breaking down when next used.
Once this cycle was established, less equipment was breaking down, which meant less emergency repairs, which meant more trades people were available to do more work during normal operating hours. Eventually all routine maintenance was done in the regular working day. We also enabled (trained) the operators to do some basic everyday maintenance tasks and to take some simple measurements. This freed up time for the skilled trades during their prime shifts.
There was one unexpected side effect. The trades people over the years had grown to expect a significant portion of their income to come from overtime work. As we were able to transfer the maintenance work from the weekends into the normal working day, the company saw a significant reduction in overtime costs. This, of course, meant that the trades people saw a drop in their pay packets.
All efforts toward the perfect plant will both positively and negatively affect your staff. Don’t forget the human element — always consider the impact on your most important asset, your people. Unfortunately, in this case, there wasn’t much we could do to mitigate the lower paychecks. We did try to give what little overtime there was to the worst cases. If we had thought through the full ramifications of the implementation, we could have informed the trades people long before the impact was felt so they could plan their finances accordingly.
A never-ending journey
As you realize your vision of the perfect plant, what was a dream of perfection becomes today’s reality — and brings all the problems that reality entails. What’s interesting is that this new reality, along with its new problems, offers the opportunity to create a vision of the "new" perfect plant. Today’s vision is tomorrow’s reality. A continual renewal process is part of the perfect plant.
Just as all companies, even within the same industry, differ, so, too, does each’s vision of the "perfect plant." Everyone sees their problems with different importance and urgency.
For example, Nova Chemicals primarily wanted to address three problems:
- executives’ limited visibility into manufacturing capacity constraints and their impact on margins;
- production personnel’s and business line managers’ lack of real-time visibility into performance deviations and their financial impact; and
- data inaccuracies because ERP and plant systems were not connected.
By implementing part of its vision of the perfect plant with SAP xMII (SAP Manufacturing Integration and Intelligence) and Pavilion xMPO, Nova was able to:
- achieve more predictable performance;
- make better decisions on product mix to maximize profitability; and
- take new, more profitable orders by having real-time insight into capacity and contribution margin.
Some of the benefits included:
- millions of dollars in savings from higher productivity and asset utilization;
- quick identification by management of opportunities for higher margins and profits;
- access to data in real-time for more informed decisions; and
- better motivation and tools for operators to maximize efficiencies and close the gap between theoretical and actual capacity.
On the other hand, Eastman Chemical had a different emphasis:
- freeing employees from serving as data integrators who manually collect data from multiple systems; and
- achieving a "single version of the truth" enterprise-wide based on "right time" actionable data intelligence.
Using SAP xMII and integrating it into its mySAP ERP system, the company gained a number of benefits, including:
- anticipated savings totaling more than $10 million in inventory, procurement and other areas due to improved use of data as information;
- reduction in consignment inventory by 8% in the first month and by 23% as of May 2006; and
- 50% drop in emergency consignment shipments through better inventory tracking.
Take the first step
The quest, like all great journeys or adventures, looks overwhelming in the beginning. However, you have to start somewhere. Decide on what makes your perfect plant. Find the areas in your current plant processes where you don’t meet your vision. Quantify the expected benefits in these areas. Determine prioritization criteria — for instance, time to implement, difficulty, cost, expected benefit and benefit/cost — and the priorities for these areas of improvement. Then start your journey. Be sure to celebrate each success, for the journey can be a long one.
John Harrison is a senior solution architect in the Chemical Industry Business Unit of SAP Canada, Toronto. E-mail him at email@example.com.