add support for manufactured product also
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@ -9,7 +9,7 @@
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redistributing the cost to COGS and Inventory.
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""",
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'author': 'Suherdy Yacob',
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'depends': ['stock_account', 'account'],
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'depends': ['stock_account', 'account', 'mrp'],
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'data': [
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'security/ir.model.access.csv',
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'data/ir_sequence_data.xml',
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@ -103,9 +103,12 @@ class StockReadjustValuation(models.Model):
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# Re-run initial stock just in case dates changed
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self._compute_initial_stock()
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# 1. Reset & Load Base Vendor Data
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# We separate Vendor (Immutable) from Mfg (Mutable)
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vendor_data = {} # {product_id: (qty, value)}
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for line in self.line_ids:
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# 2. Purchases (Start <= Date <= End)
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# Find incoming layers
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# Vendor Incoming Layers
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incoming_layers = self.env['stock.valuation.layer'].search([
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('product_id', '=', line.product_id.id),
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('create_date', '>=', self.date_start),
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@ -114,18 +117,130 @@ class StockReadjustValuation(models.Model):
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('stock_move_id.location_id.usage', '=', 'supplier'), # From Vendor
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('company_id', '=', self.company_id.id)
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])
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v_qty = sum(incoming_layers.mapped('quantity'))
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v_val = sum(incoming_layers.mapped('value'))
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vendor_data[line.product_id.id] = (v_qty, v_val)
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line.purchase_qty = sum(incoming_layers.mapped('quantity'))
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line.purchase_value = sum(incoming_layers.mapped('value'))
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# 3. Calculate Weighted Average
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total_qty = line.qty_counted + line.purchase_qty
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total_value = line.target_initial_value + line.purchase_value
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# Initialize with Vendor Data only first
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line.purchase_qty = v_qty
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line.purchase_value = v_val
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# Initial Average calc
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total_qty = line.qty_counted + v_qty
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total_value = line.target_initial_value + v_val
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if not float_is_zero(total_qty, precision_rounding=line.product_id.uom_id.rounding):
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line.new_average_cost = total_value / total_qty
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else:
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line.new_average_cost = 0.0
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line.new_average_cost = line.product_id.standard_price
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# 2. Iterative Cost Rollup (for Manufacturing)
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# We loop to allow lower-level component cost changes to propagate to higher-level FGs
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# 3 iterations should be sufficient for most chains in a retrospective batch
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for _ in range(3):
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# Create a localized cost map for fast lookup
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# {product_id: new_cost}
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cost_map = {l.product_id.id: l.new_average_cost for l in self.line_ids}
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changes_made = False
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for line in self.line_ids:
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# Find Incoming Mfg Layers (Production -> Stock)
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mfg_layers = self.env['stock.valuation.layer'].search([
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('product_id', '=', line.product_id.id),
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('create_date', '>=', self.date_start),
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('create_date', '<=', self.date_end),
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('quantity', '>', 0),
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('stock_move_id.location_id.usage', '=', 'production'), # From Production
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('company_id', '=', self.company_id.id)
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])
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if not mfg_layers:
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continue
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# Calculate New Value for these MOs
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# We need to look at the MOs linked to these moves
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moves = mfg_layers.mapped('stock_move_id')
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production_ids = moves.mapped('production_id')
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total_mfg_qty = 0
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total_mfg_value = 0
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for production in production_ids:
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# Calculate Cost of this specific MO
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# Cost = Components + Operations
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# 1. Components
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comp_cost = 0
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for raw_move in production.move_raw_ids.filtered(lambda m: m.state == 'done'):
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# Use NEW cost if available, else Standard Price
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p_id = raw_move.product_id.id
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price = cost_map.get(p_id, raw_move.product_id.standard_price)
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comp_cost += raw_move.product_uom_qty * price
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# 2. Operations (Workcenters) - Assume standard logic didn't change (immutable for now)
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# We can fetch the 'value' from the original valuation layer?
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# No, we must recalculate or look at existing cost share.
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# Simplified: We assume Operation Cost is preserved from original recording?
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# Or simpler: We don't touch Op Cost, we only readjust Material Cost.
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# But how to get "Original Op Cost" easily?
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# We can diff the Original Layer Value vs Original Component Value?
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# That's complicated.
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# Alternative: We just re-sum everything?
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# Let's check if we can get operation cost.
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# Usually stored in analytic lines or just captured in the layer?
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# For V17, stock.valuation.layer has the total value.
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# If we simply recalculate material, we might lose overheads if we don't include them.
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# SAFE BET:
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# Get Original Unit Cost of MO = Layer Value / Layer Qty.
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# Get Original Material Cost.
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# Difference = Overhead.
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# New Cost = New Material + Overhead.
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# Let's try to preserve Overhead.
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# Original Layer for this MO (Output)
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orig_output_layers = self.env['stock.valuation.layer'].search([('stock_move_id.production_id', '=', production.id), ('quantity', '>', 0)])
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orig_val = sum(orig_output_layers.mapped('value'))
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orig_qty = sum(orig_output_layers.mapped('quantity'))
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if orig_qty == 0: continue
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# Original Material Cost (from Moves)
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# We sum the ABSOLUTE value of raw moves
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orig_raw_val = sum([abs(m.value) for m in production.move_raw_ids if m.state == 'done'])
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overhead_val = orig_val - orig_raw_val
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# New Material Cost
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# Calculated above as `comp_cost`
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new_mo_total_value = comp_cost + overhead_val
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# Add to totals
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total_mfg_qty += orig_qty
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total_mfg_value += new_mo_total_value
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# Update Line
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v_qty, v_val = vendor_data.get(line.product_id.id, (0, 0))
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line.purchase_qty = v_qty + total_mfg_qty
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line.purchase_value = v_val + total_mfg_value
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# Recalculate Average
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total_qty = line.qty_counted + line.purchase_qty
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total_value = line.target_initial_value + line.purchase_value
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prev_avg = line.new_average_cost
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if not float_is_zero(total_qty, precision_rounding=line.product_id.uom_id.rounding):
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line.new_average_cost = total_value / total_qty
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else:
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line.new_average_cost = 0.0
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if abs(line.new_average_cost - prev_avg) > 0.01:
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changes_made = True
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if not changes_made:
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break
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self.state = 'calculated'
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@ -200,6 +315,161 @@ class StockReadjustValuation(models.Model):
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if not float_is_zero(diff, precision_digits=2):
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self._create_correction_from_move(move, diff)
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# Global Cost Map (Product ID -> New Cost)
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# This map contains the new_average_cost for all products in the batch.
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cost_map = {l.product_id.id: l.new_average_cost for l in self.line_ids}
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for line in self.line_ids:
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# 4. Readjust Manufacturing Output (Incoming MOs)
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# We need to correct the value of the Finished Good entering stock
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# based on the new cost of components.
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mfg_layers = self.env['stock.valuation.layer'].search([
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('product_id', '=', line.product_id.id),
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('create_date', '>=', self.date_start),
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('create_date', '<=', self.date_end),
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('quantity', '>', 0), # Incoming
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('stock_move_id.location_id.usage', '=', 'production'), # From Production
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('company_id', '=', self.company_id.id)
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])
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mfg_moves = mfg_layers.mapped('stock_move_id')
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for move in mfg_moves:
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production = move.production_id
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if not production: continue
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# Re-Calculate MO Cost (Components New Cost + Overhead)
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comp_cost = 0
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for raw_move in production.move_raw_ids.filtered(lambda m: m.state == 'done'):
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p_id = raw_move.product_id.id
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# Use NEW cost from cost_map if available, else Standard Price
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price = cost_map.get(p_id, raw_move.product_id.standard_price)
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comp_cost += raw_move.product_uom_qty * price
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# Overhead Preservation
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# Get total original output value for the entire MO
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all_output_layers_for_mo = self.env['stock.valuation.layer'].search([('stock_move_id.production_id', '=', production.id)])
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all_output_val_for_mo = sum(all_output_layers_for_mo.mapped('value'))
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# Original Material Cost (from Raw Moves for the entire MO)
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orig_raw_val_for_mo = sum([abs(m.value) for m in production.move_raw_ids if m.state == 'done'])
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overhead_total = all_output_val_for_mo - orig_raw_val_for_mo
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# New Total Cost for the entire MO
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new_total_cost_for_mo = comp_cost + overhead_total
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# Target Value for THIS specific move (proportion of total MO cost)
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target_value = 0.0
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if production.qty_produced > 0:
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ratio = move.product_uom_qty / production.qty_produced
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target_value = new_total_cost_for_mo * ratio
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# Current Value of THIS move (sum of all layers for this move)
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current_val = sum(self.env['stock.valuation.layer'].search([('stock_move_id', '=', move.id)]).mapped('value'))
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diff = target_value - current_val
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if not float_is_zero(diff, precision_digits=2):
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# Create Correction
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# Original Move: Dr Stock, Cr WIP
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# Find accounts from original move's account_move_ids
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# We need to find the account move linked to the original stock move
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original_am = move.account_move_ids.filtered(lambda am: am.state == 'posted')
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if not original_am:
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# Fallback: try to find an SVL for this move that has an account move
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original_svl_with_am = self.env['stock.valuation.layer'].search([
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('stock_move_id', '=', move.id),
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('account_move_id', '!=', False)
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], limit=1)
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if original_svl_with_am:
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original_am = original_svl_with_am.account_move_id
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if not original_am:
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_logger.warning("Could not find original account move for stock move %s to determine accounts for MO adjustment.", move.name)
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continue # Skip if can't find accounts
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am_lines = original_am.line_ids
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# Find Stock Account (usually debit for incoming)
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stock_acc_id = line.product_id.categ_id.property_stock_valuation_account_id.id
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stock_line = am_lines.filtered(lambda l: l.account_id.id == stock_acc_id)
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# Find WIP Account (usually credit for incoming)
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wip_acc_id = False
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# Try to find the credit line that is not the stock account
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wip_line = am_lines.filtered(lambda l: l.credit > 0 and l.account_id.id != stock_acc_id)
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if wip_line:
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wip_acc_id = wip_line[0].account_id.id
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else:
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# Fallback: try to find the stock production location's valuation_out_account_id
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prod_location = self.env['stock.location'].search([('usage', '=', 'production')], limit=1)
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if prod_location and prod_location.valuation_out_account_id:
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wip_acc_id = prod_location.valuation_out_account_id.id
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if not (stock_acc_id and wip_acc_id):
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_logger.warning("Could not determine stock or WIP accounts for MO adjustment for move %s.", move.name)
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continue # Skip if accounts not found
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# Construct Account Move
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# If diff > 0 (Value Up): Dr Stock, Cr WIP
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debit_acc = stock_acc_id
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credit_acc = wip_acc_id
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amt = diff
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if diff < 0:
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# If diff < 0 (Value Down): Dr WIP, Cr Stock
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debit_acc = wip_acc_id
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credit_acc = stock_acc_id
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amt = abs(diff)
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description = _("Readjustment MO: %s") % production.name
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move_vals = {
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'journal_id': self.journal_id.id,
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'date': self.date_end.date(),
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'ref': f"{self.name} - {description}",
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'move_type': 'entry',
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'line_ids': [
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(0, 0, {
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'name': description,
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'account_id': debit_acc,
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'debit': amt,
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'credit': 0,
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'product_id': line.product_id.id,
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}),
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(0, 0, {
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'name': description,
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'account_id': credit_acc,
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'debit': 0,
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'credit': amt,
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'product_id': line.product_id.id,
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}),
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]
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}
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ac_move = self.env['account.move'].create(move_vals)
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ac_move.action_post()
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self.account_move_ids = [(4, ac_move.id)]
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# Create SVL
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svl_vals = {
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'company_id': self.company_id.id,
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'product_id': line.product_id.id,
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'description': description,
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'stock_move_id': move.id,
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'quantity': 0,
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'value': diff, # Value is positive for increase, negative for decrease
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'account_move_id': ac_move.id,
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}
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new_svl = self.env['stock.valuation.layer'].create(svl_vals)
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# Force Date
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self.env.cr.execute('UPDATE stock_valuation_layer SET create_date = %s WHERE id = %s', (move.date, new_svl.id))
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self.env.cr.execute('UPDATE account_move SET date = %s WHERE id = %s', (self.date_end.date(), ac_move.id))
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self.state = 'done'
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def _create_correction_from_move(self, move, amount):
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